A CLOSE LOOK AT TECHNOLOGY ACCEPTANCE: A PHENOMENOLOGICAL
STUDY
A Dissertation
by
JASON BRYAN MOATS
Submitted to the Office of Graduate and Professional Studies of
Texas A&M University
in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
Chair of Committee,
Committee Members,
Head of Department,
Jia Wang
Fred M. Nafukho
Robert Strong
Ben Welch
Fred M. Nafukho
December 2013
Major Subject: Educational Human Resource Development
Copyright 2013 Jason Bryan Moats
ABSTRACT
The purpose of this research study was to explore the phenomenon of public
safety professionals using innovative technology in a public safety training context. A
single question guided this research: What is the experience of public safety trainees who
are required to use innovative or emerging technology in face-to-face training?
I employed a qualitative, hermeneutic phenomenological research approach to
conduct this study. The approach included in-depth interviews with six public safety
professionals to better understand their experience as they encountered innovative
technology in training contexts. Participants were identified through purposeful
sampling focusing on public safety professionals who attended training that incorporated
innovative technology conducted in the United States. The primary data sources for this
qualitative study were in-depth interviews with open-ended questions and supporting
data from observation and documents to provide a contextual frame.
The findings of this study provided several implications to human resource
development. For practitioners, the findings offer valuable information that will
potentially enable effective integration of innovative technologies in training. The
findings provide opportunities for researchers to explore the impact of different
technologies used on trainees’ technology acceptance process. Finally, the findings
provide a potential to develop new theories to explain how the acceptance of innovative
technology occurs.
ii
DEDICATION
This dissertation is dedicated to three groups of people who have been at the core
of my life. First, I dedicate this to my parents, Robert and Kathy Moats, who have
served as examples of the best in training and educating adults and gave me my start in
the field. The second group is my wife and children. Michelle, Todd, Mikayla, Calista,
and Marissa have given me permission to be absent from so much while I studied,
struggled, and wrote. Finally, this dissertation is dedicated to those who respond to the
emergencies throughout the world. These professionals put their lives on the line every
day to protect us—some for pay, some not—nevertheless, they do it all for us. To all of
you, I offer my sincere and complete thanks.
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ACKNOWLEDGEMENTS
I would like to thank my committee chair, Dr. Jia Wang, and my committee
members, Dr. Robert Strong, Dr. Ben Welch, and Dr. Frederick Nafukho, for their
guidance, support, and most importantly their patience throughout this entire process. In
addition, I would be remiss if I did not thank Dr. Toby Marshall Egan, Dr. Larry Dooley,
Dr. Homer Tolson, Dr. Sue Lyhnam, and Dr. Gary McLean whose guidance and tutelage
have been invaluable throughout this seven year journey.
I also would like to thank my colleagues and the leadership at the Texas A&M
Engineering Extension Service/Emergency Service Training Institute (TEEX/ESTI).
Without their assistance, encouragement, and permission, this research study would not
have been possible. I also offer a special thank you to my friends and fellow students at
Texas A&M University. The Thursday Night Writing Group rarely met on Thursday
nights and often when we did meet we did not write; but we did work through many
things, shed a few tears, and cussed the hurdles along our individual and collective
journeys. Without you—and you know who you are—this research would be no more
than a clanging gong!
I would also be remiss if I did not recognize a great group of people: the
Academy of Human Resource Development. This is where I have found my
professional association home for the last eight years and will for many more. I could
not have completed this without the support and encouragement from the ScholarPractitioner Special Interest Group (SIG). While informally our motto has been “We’ll
iv
be at the bar,” I have truly been blessed by the scholarship and collegiality of this fine
group of scholar-practitioners. Equally, I owe many thanks to the staff and faculty at
Texas A&M University, especially in the Educational Human Resource Development
Program. Without their patience, guidance, coaching, and mentoring, this
accomplishment would not have been possible.
Finally, I offer my sincere gratitude and love to my family: my partner of more
than 20 years, Michelle, and our four children, Todd, Mikayla, Calista, and Marissa.
These people have been nothing short of an amazing group of heroes throughout the last
decade as I have pursued multiple degrees. Their love, support, encouragement, and
inspiration have kept me going through the rough times and motivated me to finish.
They have always pushed me to go beyond what I thought was possible. For this and
much more, I am grateful.
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TABLE OF CONTENTS
Page
ABSTRACT ...................................................................................................................... ii
DEDICATION ................................................................................................................. iii
ACKNOWLEDGEMENTS ..............................................................................................iv
TABLE OF CONTENTS ..................................................................................................vi
LIST OF FIGURES ............................................................................................................x
LIST OF TABLES ............................................................................................................xi
CHAPTER I INTRODUCTION ...................................................................................... 12
Background of the Study ...........................................................................12
The Problem ............................................................................................... 16
Innovative and Emerging Technology ...............................................17
Purpose and Research Question .................................................................21
Theoretical Context....................................................................................22
Unified Theory of the Acceptance and Use of Technology (UTAUT)
....................................................................................................22
Change Model and Model of Managed Learning .............................. 24
Diffusion of Innovations ....................................................................25
Channel Expansion Theory ................................................................ 26
Significance of the Study ...........................................................................26
Boundary of the Study ...............................................................................28
Definitions .................................................................................................28
Organization of the Dissertation ................................................................ 30
CHAPTER II REVIEW OF LITERATURE ....................................................................31
Public Safety Training ...............................................................................32
Training .............................................................................................. 32
Public Safety Professionals ................................................................ 36
Types of Public Safety Training ........................................................ 39
Technology Used in Public Safety Training ......................................40
Technology Acceptance .............................................................................42
Theory of Reasoned Action (TRA) ....................................................43
Technology Acceptance Model (TAM) .............................................44
The Unified Theory of Acceptance and Use of Technology (UTAUT)
....................................................................................................45
vi
Change .......................................................................................................47
Change Theory in the Field and in the Classroom ............................. 48
Diffusion of Innovations ....................................................................51
Channel Expansion Theory ................................................................ 57
Digital Personalities: The Immigrants, Natives, and Settlers ....................59
Chapter Summary ...................................................................................... 61
CHAPTER III METHODOLOGY...................................................................................62
Restatement of the Purpose and Research Question ..................................62
Research Paradigm ....................................................................................63
Social Constructivism ........................................................................64
Rationale for a Phenomenological Approach ....................................65
Methodology: The Hermeneutic Phenomenological Approach ................67
Methods .....................................................................................................69
Sampling Procedure ...........................................................................69
Data Collection ..................................................................................73
Data Analysis ..................................................................................... 75
Ethical Issues ............................................................................................. 80
Trustworthiness .......................................................................................... 81
Credibility .......................................................................................... 81
Transferability ....................................................................................84
Dependability ..................................................................................... 84
Confirmability ....................................................................................85
Role of the Researcher ...............................................................................86
Researcher’s Position .........................................................................86
Chapter Summary ...................................................................................... 88
CHAPTER IV FINDINGS ............................................................................................... 90
The Training Context .................................................................................91
The Computer-based Simulation ....................................................... 91
iPads ...................................................................................................92
Participant Profiles ..................................................................................... 92
Everett ................................................................................................ 93
Juan ....................................................................................................97
Terrence ........................................................................................... 100
Rusty ................................................................................................ 102
Bobby ............................................................................................... 103
Teresa ............................................................................................... 105
Categories and Themes ............................................................................107
Perceptions of Technology............................................................... 107
Experiences with Technology .......................................................... 120
Facilitators of Technology Acceptance............................................124
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Barriers to Technology Acceptance .................................................127
Other Themes of Importance ........................................................... 131
Chapter Summary .................................................................................... 138
CHAPTER V DISCUSSION, RECOMMENDATIONS, AND CONCLUSIONS .......139
Discussion ................................................................................................ 139
Conclusion #1. An Individual’s Perception of Innovative Technology
in a Training Context Influences His or Her Decision About
Accepting or Rejecting the Technology ...................................142
Conclusion #2. Individuals’ Learning Anxiety is Intensified When
Using Innovative Technology in a Training Context ...............144
Conclusion #3. Exposure to and Early Success in Using Innovative
Technology Are Essential to the Individual’s Continued Use of it
in a Training Context ................................................................ 145
Conclusion #4. Individuals Must Experience the Utility of Innovative
Technology to Continue Using it in a Training Context ..........147
Conclusion #5. Role Models’ Play a Key Role in Individual’s
Continued Use of Innovative Technology in a Training Context
..................................................................................................148
Conclusion #6. An Individual’s Digital Personality Does Not Appear
to Influence Technology Use in a Training Context.................150
A New Conceptual Framework ............................................................... 151
Stage 1: Excitement .........................................................................155
Stage 2: Anxiety ...............................................................................155
Stage 3: Interaction With the Technology .......................................156
Stage 4: Usability Evaluation ........................................................... 157
Stage 5: Decision to Accept ............................................................. 158
Stage 6: Acceptance .........................................................................159
Researcher’s Reflection ...........................................................................161
The Impact of My Biases .................................................................161
Contradictions ..................................................................................163
Recommendations for Practice ................................................................ 164
Understand That Participants Will Be Anxious About Using the
Technology and Address It ....................................................... 165
Let Them Experience the Utility: Provide Meaningful Opportunities
for Participants to Interact With the Technology in a Training
Context ...................................................................................... 166
Avoid Distractions: Do Not Use Technology for Technology’s Sake
..................................................................................................168
Recommendations for Research .............................................................. 168
Conclusion ............................................................................................... 171
REFERENCES ...............................................................................................................174
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APPENDIX A ................................................................................................................187
APPENDIX B ................................................................................................................189
APPENDIX C ................................................................................................................190
APPENDIX D ................................................................................................................191
APPENDIX E .................................................................................................................192
APPENDIX F .................................................................................................................193
APPENDIX G ................................................................................................................194
APPENDIX H ................................................................................................................197
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LIST OF FIGURES
Page
Figure 1. Theoretical framework for the study................................................................ 32
Figure 2. Basic conceptual framework underlying user acceptance models. .................. 46
Figure 3. A model of five stages in the innovation-decision process. ............................ 53
Figure 4. A progression of the individuals’ perceptions of technology ........................ 143
Figure 5. A new conceptual framework that illustrates the process experienced by
individuals encountering innovative technologies. ........................................ 154
x
LIST OF TABLES
Page
Table 1 Emergency Responder Disciplines and Descriptions ......................................... 37
Table 2 Profiles of Participants ........................................................................................ 94
Table 3 Summary of Major Findings ............................................................................. 108
Table 4 Summary of Six Conclusions of the Study ....................................................... 141
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CHAPTER I
INTRODUCTION
Learning opportunities can be a transformational experience in a person’s life
(Cranton, 2002 ; Mezirow, 1991); however, they can also be anxiety-ridden and
frustrating experiences (Schein, 1996). These experiences have the potential to sweeten
or sour future learning opportunities. Therefore, the process of creating learning
opportunities that reach ever increasingly diverse audiences must be undertaken with the
greatest care possible.
This process involves teamwork between instructional designers, technical
writers, subject matter experts, managers, and instructors. It also involves a creative
blending of words, concepts, and best practices to create meaningful, productive
experiences for the audience. In addition, technology can be blended into the course
design to enhance the learning experience, make the learning opportunity more efficient,
or even teach individuals how to use the particular technology on the job. However, the
added complexity of technology comes with its own set of challenges and anxiety. The
focus of this research is to study the phenomenon of technology acceptance through an
exploration of individuals’ experience as they use innovative technology to facilitate
training.
Background of the Study
To be successful, instructors must breathe life into courses so that they engage
participants, regardless of the course delivery medium (i.e., in a traditional classroom,
online, or some combination) (Larsen, Sanders, Astray, & Hole, 2008). Therefore, they
12
must have technical knowledge and skills to operate and incorporate the technology used
in the classroom (Callahan, 2010; McGurn & Prevou, 2012) and then be able to sell the
use of that technology to participants. In addition, courses must educate, engage, and
increasingly entertain the participants. In other words, courses must create a vehicle for
“edutainment” (Junginger, 2008, p. 20). To accomplish this, instructional designers
must develop training courses and programs that meet the needs of individuals and
organizations and also engage and entertain participants (McGurn & Prevou, 2012).
Finally, innovative and emerging technology must be successfully integrated into
training, despite the technological diversity of the workforce. Innovative technologies
are those technologies or the use of technologies employed in training and “perceived as
new by an individual” (Rogers, 2003, p. 12). Emerging technologies are new
technologies that are employed in training. Examples of these technologies include
using tablets and electronic books to replace hard copy textbooks and computer-based
simulations to replicate real-world activity.
Workforce diversity may be explained on many different planes; however, an
important and often-neglected measure of workforce diversity is the workforce’s
comfort and familiarity with innovative and emerging technologies (Prensky, 2001b,
2001c; Tapscott, 2009). Understanding the technological diversity within the workforce
provides insight into understanding how individuals may react to innovative and
emerging technology used in training. Therefore, this information is essential to
instructional designers, managers, and instructors as they create learning opportunities.
13
Palfrey and Gasser (2008) provide categories to describe this digital diversity:
digital immigrants, digital natives, and digital settlers. These categories are best
described as digital personalities. Digital immigrants are hesitant adopters of the
Internet and other related technologies. Digital settlers are positioned between digital
immigrants and digital natives. They are identified as people who are not digital natives,
but have a sophisticated use of technologies while continuing to rely heavily on other
analog forms of interaction. Digital natives are people who have access to networked
digital technologies, possess strong computer skills, and share a common culture that is
not defined by age. Instead, the digital native status is strongly influenced by peoples’
exposure and interactions with technologies, their culture, people outside of the culture,
and institutions.
The determination of which category an individual fits into is related to the
individual’s exposure and interaction with technology. Given the ubiquitous nature and
variety, as well as the overwhelming amount of technology in the United States, it is
easy to see why much of the emerging U.S. workforce would be considered digital
natives (Tapscott, 2009). In contrast, the established workforce is made of a potpourri of
early digital natives, digital settlers, and digital immigrants. Moreover, those who
choose the training format in organizations are more likely to be digital immigrants or
settlers.
Not surprisingly, this diversity of training consumers creates significant
dissonance. Not only is there a dissonance among those who plan and those who receive
training, but there is also dissonance between the aforementioned groups of those who
14
receive training. In many cases, this dissonance is centered on how technology is used
in training and education (Callahan & Sandlin, 2007; Gabriel, 2008; Tapscott, 2009).
The outcome of this dissonance results in missed expectations and frustration. Rossett
and Marshall (2010) report that “[training] opportunities are being left on the table” (p.
7) because organizations are not taking advantage of the pervasiveness of innovative
technologies to enhance training. Examples of these technologies can include webenabled smartphones, e-readers, tablets, and computer-aided simulation (to name a few).
Conversely, others, such as Callahan and Sandlin (2007), suggest that technology has
hindered learning and, therefore, resulted in poor performance. It is my contention that
the core of this debate rests in a user’s willingness to adopt an innovative technology in a
training application. In other words, the issue is not only the appropriate use or non-use
of technology in training; it is the user’s acceptance of the technology used in training.
For the purposes of this study, the terms technology acceptance and adoption are
interchangeable and refer to an individual deciding to use a technology to the fullest
extent possible within the given application (Rogers, 2003).
A key question for the training development team is: If organizations incorporate
innovative technology into training opportunities but learners reject the technology, has
the organization succeeded in developing effective training? I suggest the answer is no
and that the organization has failed to effectively meet the needs of the user. Ultimately,
organizations could become irrelevant if they fail to develop training that meets the
needs and expectations of the learners (Tapscott, 2009). Palfrey and Gasser (2008)
capture the essence of the dilemma very succinctly, “…we are at a crossroads. There are
15
two possible paths before us – one in which we destroy what is great…and one in which
we make smart choices and head toward a bright future…”(p. 7)(p. 7).
The Problem
Challenges exist to creating effective training courses and programs. First,
employers and employees often exhibit negative attitudes toward employee training
(Panagiotakopoulos, 2011). This may be due to many participants’ fear of performing
poorly in training or a lack of self-confidence in their performance during training
(Holley & Dobson, 2008). Another challenge exists because of limits placed on
employees’ available time and accessibility to training resources (Callahan & Sandlin,
2007; Lyons & Mattare, 2011; Panagiotakopoulos, 2011). For example, when
organizations face an economic crisis, the time that would be available for training is
sacrificed for productivity. This is very apparent in municipal governments that are
reducing funding to fire, law enforcement, public works, and other public service
agencies (Greenstone & Looney, 2011; Johnson, Oliff, & Williams, 2011; Shannon,
2011). Complicating the accessibility issue, many government agencies are limited by
travel restrictions, which allow personnel to attend training delivered only within their
city or neighboring cities. Consequently, agencies must rely on internal and grantfunded training to provide the bulk of their training. In other cases, agencies are simply
doing without training.
The cost of developing, delivering, and maintaining training is another
significant challenge faced by organizations (Callahan & Sandlin, 2007;
Panagiotakopoulos, 2011). The current economic crisis has created financial challenges
16
for many organizations, regardless of their size. The net result is that most organizations
are forced to do more with less, as illustrated with the release of the 2010 U.S. Gross
Domestic Product (GDP), which showed a 2.5% increase while the unemployment rate
hovered at nearly the highest rate in more than a decade (BEA, 2011).
Because of these and other challenges, organizations are constantly seeking
efficiencies that increase the accessibility to training while reducing its cost. Innovative
technologies can provide these efficiencies. For example, the use of web-based and Web
2.0 technology-based learning applications enable the wide-spread reusability and
accessibility of the training, in both temporal and geographical terms (ASTD, 2010).
The result is a single input with multiple, reusable outputs that can be accessed nearly
anywhere there is a computer and an Internet or wireless connection; however, Rossett
and Marshall (2010) maintain that organizations are not fully taking advantage of the
pervasiveness of innovative technologies to enhance training. At the end of their
analysis, the authors ask, “Should we lament that the habits identified in this study are
not much different in 2009 than they were in 1989 (although, of course, enabled by
technology)?” (Rossett & Marshall, 2010, p. 38).
Innovative and Emerging Technology
Technology constantly emerges and inspires innovation (Rogers, 2003).
Moreover, the use of innovative and emerging technology has revolutionized education
(Frey & Faul, 2005), and by extension, training and development. Technological
innovations, from books to the slate blackboard, erasable white boards to tablet
computers, computer-based learning management systems to high fidelity simulations,
17
and Facebook to Twitter, have significantly impacted the ability and capacity to conduct
effective training (McWhorter, 2010). Innovative technology is defined as technology
that is innovative or used in an innovative method. Emerging technology is defined as a
technology that is new or cutting edge; it is emerging in the marketplace. The term
innovative technology will be used throughout the rest of this manuscript to indicate both
innovative and emerging technology.
Many trainees readily accept the technological advancements and innovation;
however, sometimes trainees choose to reject the technology used to facilitate training,
likely because the benefits of learning to use the technology are not readily apparent (F.
D. Davis, 1986, 1989; F. D. Davis, Bagozzi, & Warshaw, 1989; Venkatesh, Morris,
Davis, & Davis, 2003). Rogers’s (2003) monograph, Diffusion of Innovations, provides a
basis for defining the concept of technology acceptance. Rogers (2003) explains that
when an individual encounters an innovation, he or she must ultimately make a decision
on whether to adopt (i.e., accept) or reject the innovation. In some cases, this decision
can be influenced by the social structure. In nearly all cases, there is a period of time
that must pass while the individual (or organization) works through the acceptance
process. As stated previously, technology acceptance means that an individual decides
to use a technology to the fullest extent possible within the given application (Rogers,
2003). The focus of this research study is the exploration of public safety professionals’
experiences when faced with innovative technology in a training context.
As technology grows more sophisticated, it continues to provide more value and
create opportunities for innovation in many arenas, including training (McWhorter,
18
2010). Yet, people base their decisions to adopt technology on a combination of factors
including (a) availability and access (Callahan & Sandlin, 2007), (b) the users’
perception of the appropriate use of a technology (Tapscott, 2009), (c) the perceived
utility of the technology (F. D. Davis, 1986, 1989; F. D. Davis et al., 1989; Venkatesh et
al., 2003), (d) the ease of use of the technology (F. D. Davis, 1989), and (e) the
individual’s self-efficacy, or his or her perception of how well he or she will be able to
perform in a given situation (Bandura, 1982). In other words, individuals want some
assurance that the investment they make in learning to use technology will have a return
in training and/or job performance.
Current research on the concept of technology acceptance addresses college and
university faculty accepting and using technology to teach college courses (Ahmad,
Madarsha, Zainuddin, Ismail, & Nordin, 2010; Frey & Faul, 2005), university students
adopting technology (Jonas & Norman, 2011; Liu, Chen, Sun, Wible, & Kuo, 2010), and
workers accepting technology used in the performance of their jobs (Yen, Wu, Cheng, &
Huang, 2010). Researchers have also examined the antecedents of technology
acceptance (F. D. Davis, 1986, 1989; Y. Lee, Kozar, & Larsen, 2003; Salmon, 2009;
Venkatesh et al., 2003).
However, there are voids in the research. Little if any available research
addresses the acceptance of technology used in training. Also, little if any research has
explored the aforementioned dissonance between the emerging and established
workforce. A review of available literature failed to produce studies that explore the
experiences of individuals who encounter innovative technology in a training context.
19
Studies that examine the experiences of training managers as they encounter and choose
technology to incorporate into training applications are also absent from the literature.
Prensky (2001c) asserts that these managers are typically digital immigrants and settlers
and are not as comfortable with incorporating the innovative technology into training;
moreover, they may see technology as a luxury, distraction, or frivolity (Oblinger, 2003;
Prensky, 2001b, 2006).
Research shows that digital natives are very different from any other era of
worker (Oblinger, 2003). Researchers think that a significant reason for this difference
involves the individual’s exposure to technology such as computers, video games, and
the Internet (Palfrey & Gasser, 2008; Prensky, 2001a, 2001c; Tapscott, 2009). Tapscott
(2009) writes the following about digital natives, the group he labels the Internet
Generation or Net Geners:
Net Gen kids looked at computers in the same way boomers look at TV.
Boomers don’t marvel at the technology or wonder how television transfers
audio and video through thin air…TV is a fact of life. So it has been with Net
Geners and computers. And as technology relentlessly advances each month,
young people just breathe it in... (p. 19) (p. 19)
Given this, the digital native expects to see innovative technology used in every facet of
life, including training; however, the literature has failed to produce any perspectives
that explore the experiences of digital natives as they come to these technology
acceptance decision points.
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While the dissonance between learners is intriguing, it is also troubling for
learners and organizations alike. Technology has and continues to change the world that
we live in and how we live in it (Alexander, 2009; Friedman, 2005; Kirriemuir, 2008;
Salmon, 2009). Likewise, technology and the individual’s exposure to it are changing
the training needs and expectations of the workforce (Palfrey & Gasser, 2008; Prensky,
2001a, 2001b, 2001c; Smart, Cascio, & Paffendorf, 2007; Tapscott, 2009). Therefore,
this research study is focused on understanding the phenomenon of individuals’
experience using innovative technology in a training context. Specifically, this study
explores the experiences of public safety professionals using innovative technology in a
public safety training context. In this study, the innovative technology refers to either a
computer-based, scenario-driven simulation or an e-Publication with an iPad used as an
e-Reader.
Purpose and Research Question
The challenges of making Palfrey and Gasser’s (2008) smart choices and keeping
pace with the trainees’ expectations presents serious challenges to training providers.
But without a better understanding of how and why learners accept technology, training
design and implementation decisions are likely to continue on divergent paths from the
learners’ needs (McGurn & Prevou, 2012). Swanson (as cited in Dooley & Lynham,
2003) suggests that to improve performance, instructional designers and training
managers must first understand the learners’ lived experiences as they encounter
innovative technology. In doing this, these training professionals are presented with
opportunities to better understand the learners’ perspectives and make informed
21
decisions about how to incorporate innovative technology to facilitate training in order
to foster its acceptance by the learners.
Therefore, the purpose of this research study was to explore the experience of
public safety professionals to better understand their experiences as they use innovative
technology in a public safety training context. This research study is based on a single
question: What is the experience of public safety trainees who are required to use
innovative or emerging technology in face-to-face training?
Theoretical Context
Four theories provide a theoretical context to this study: (a) Venkatesh, Morris,
Davis, and Davis’s (2003) Unified Theory of the Acceptance and Use of Technology
(UTAUT), (b) Lewin’s (1997) change model and Schein’s (1996) model of managed
learning; (c) Rogers’s (2003) diffusion of innovations, and (d) Carlson’s (1995) channel
expansion theory.
Unified Theory of the Acceptance and Use of Technology (UTAUT)
UTAUT (Venkatesh et al., 2003) was created to explain an individual’s decision
to accept and use technology in a unified way. This specific theory was derived through
a comparison and analysis of eight theoretical models of user acceptance of technology.
The basis for UTAUT was among these eight models and theories. Although these
various models have roots in systems, psychology, and sociology, each model has a
similar underlying conceptual framework for the process.
Each model presents a range of determinants numbering as few as two and as
many as seven (Venkatesh et al., 2003). As a result of the comparison of the eight
22
models, the authors theorized four primary constructs that are determinants of
technology acceptance: (a) performance expectancy or “the degree to which an
individual believes that using the system will help him or her to attain gains in job
performance,” (Venkatesh et al., 2003, p. 447); (b) effort expectancy or “the degree of
ease associated with the use of the system,” (Venkatesh et al., 2003, p. 450); (c) social
influence or “the degree to which an individual perceives that important others believe
he or she should use the new system,” (Venkatesh et al., 2003, p. 451); and (d)
facilitating conditions or “the degree to which an individual believes that an
organizational and technical infrastructure exists to support use of the system,”
(Venkatesh et al., 2003, p. 453).
Although the various theories and models had a foundation in diverse schools of
thought such as systems, psychology, and sociology, all have been shown to have a
similar underlying conceptual framework that unfolds in three steps: (1) An individual
encounters a technology and reacts to using it, (2) the user then expresses an intention to
use the technology, and (3) then the user actually uses the technology.
UTAUT and many of its underlying models and theories examined technology
acceptance from a predictive standpoint. This means that the research supporting
UTAUT examined only the determinants of technology acceptance. Consequently, these
theories and models failed to examine technology acceptance from an experiential
perspective. In other words, these theories and models failed to incorporate the richness
and depth of the user’s experiences of technology acceptance.
23
Change Model and Model of Managed Learning
Lewin (1997) provided one of the earliest models of planned change. His model
presented change in three steps: (1) unfreezing, (2) moving, and (3) refreezing. Lewin
viewed change as a modification in competing forces that hold a system’s behavior
stable (Cummings & Worley, 2005). These forces fall into two general categories:
restraining forces that desire to maintain the status quo and driving forces that desire
change. Schein (1996) adapted Lewin’s model to begin explaining managed learning.
Schein expounded on Lewin’s three-step process by explaining that the unfreezing
begins when individuals encounter disconfirming data that challenges their beliefs and
creates dissatisfaction. At this point, individuals put up defenses against change. An
important concept from Schein (1996) is “learning anxiety” (p. 29). This anxiety is a
restraining force that occurs when a learner encounters valid and relevant data that
challenges what was once held to be true. It originates from a sense or threat of loss.
Individuals must overcome the learning anxiety to advance to the next step of change,
moving.
Schein (1996) suggests that the move stage is defined by a “cognitive
redefinition” (p. 30) in which words take on a different meaning, the conceptual
interpretations are broadened, and the scale of judgment shifts. This redefinition process
concludes through one of two mechanisms: “(1) learning through positive or defensive
identification with some available positive or negative role model or (2) learning through
a trial-and-error process based on scanning the environment for new concepts” (Schein,
1996). As the new concepts are accepted, the refreezing occurs. Both Lewin’s (1997)
24
change model and Schein’s (1996) adaptation inform the conceptual framework that
guided this study.
Diffusion of Innovations
Rogers’s (2003) diffusion of innovation is the seminal work on how innovations
are adopted in a social system over time. Rogers first published his book more than five
decades ago to explain how agricultural innovations were adopted based on his research
of Ohio farmers. Over the last five decades the diffusion of innovations has been
applied to many fields, including health, technology, and education.
Rogers (2003) defines diffusion as “a process by which an innovation is
communicated through certain channels over time among members of a social system”
(p.11). Rogers (2003) defines an innovation as “an idea, practice, or object that is
perceived as new by an individual or other unit of adoption” (p. 12). The focus of this
study was not limited to the acceptance of any technology. In fact, this study was
interested in how innovative technology with a specific application—supporting the
delivery of training—was accepted by trainees.
One of the most powerful contributions of this work is the innovation-decision
process. This five-step model attempts to explain how individuals pass from getting
information to making a decision about using an innovation. Through this process, an
individual passes through a “series of choices and actions over time” (Rogers, 2003, p.
168) toward making a decision to accept or reject the innovation. Understanding a
process of how innovations are communicated throughout a social system helps inform
this study.
25
Channel Expansion Theory
Channel expansion theory (Carlson, 1995; Carlson & Zmud, 1999) arose in
response to the inadequacies of other theories to explain how individuals chose
communication channels, particularly technology channels. This theory compliments
the diffusion of innovations by explaining how communications channels within a social
system are chosen. This theory suggests that users are able to expand the richness of a
channel by increasing familiarity with the channel (Carlson, 1995), lending credence to
the suggestion that the more experience an individual has with a particular channel (i.e.,
technology), the more likely he or she is to use (i.e., accept) the channel. From this, it is
reasonable to extrapolate that the more experience an individual has with a technology,
the more likely he or she is to accept the technology.
Significance of the Study
A review of the extant literature reveals that research on the topic of technology
acceptance has explored the probable conditions for individuals accepting technology
from a quantitative approach. Additionally, this research has provided a basic sequence
of acceptance. Yet, the extant research fails to provide a qualitative approach to explore
the rich descriptions of individuals’ experiences as they use innovative technology.
Similarly, the extant literature concerning change explains a process of change,
including change through learning. However, change is rarely mentioned in technology
acceptance and the impact of the complexities of technology are rarely mentioned in
change literature. Moreover, the diffusion of innovation literature explains how
26
innovation is diffused throughout an organization and even a culture. Yet, the literature
does not clearly discuss how individuals adopt innovation.
This study provides both practical and theoretical contributions to the field of
human resource development by exploring the lived experiences of public safety
professionals as they use innovative technology in a public safety training context. This
information is valuable to the instructors and designers of training who must incorporate
technology into training applications; this information will also better inform the training
managers who assess the value and choose training for diverse audiences.
With regard to the theoretical significance, this study adds to the understanding
of the underpinnings of technology acceptance, which is likely the instructional design
employed to create the training course and change. The focus on the trainees’
experience from an interpreter’s perspective, regardless of their position within the
digital diversity, fills a gap in the extant literature.
The practical significance of this study lies within the information provided to
instructional designers and instructors. This information gives them more information
about how to properly incorporate and sell technology used within training applications.
In other words, the information can provide those responsible for designing and
delivering training the knowledge needed to more effectively incorporate technology
into training applications. Ultimately, this knowledge can improve the design of training
and the learners’ acceptance of technology. This knowledge may also provide the keys
that begin to bridge the gap between digital immigrants, digital settlers, and digital
natives.
27
Boundary of the Study
All research is limited by a multitude of factors. This study is bounded to
selected participants in courses delivered by one organization due to constraints in time,
financial resources, and access to organizations using innovative technologies in training
public safety personnel. The selection of both the research site and participants
represents a method of purposeful sampling (Creswell, 2007; Merriam, 1998; Patton,
2002). The participants in this study were public safety trainees and the organization
under investigation was a training organization for public safety employees. Given the
convenience of access, I selected the largest public safety training organization in the
United States. Participant selection is also based on predetermined criteria, which are
discussed in Chapter III. As I previously stated, my intent was to develop an in-depth
understanding of public safety trainees’ experiences as they were confronted with
innovative technology. As such, any generalization of this study’s findings should be
done with caution. Finally, in qualitative research, the researcher is the instrument. As
that instrument, I brought my own set of assumptions to this study.
Definitions

Digital native:
A person born into the digital age (after 1980) who has access to
networked digital technologies and strong computer skills and
knowledge. Digital natives share a common global culture that is defined
not strictly by age but by certain attributes and experiences related to how
they interact with information technologies, information itself, one
28
another, and other people and institutions. (Palfrey & Gasser, 2008, p.
346)

A digital immigrant is “[a] person who has adopted the internet and related
technologies, but who was born prior to the advent of the digital age” (Palfrey &
Gasser, 2008, p. 346)

An electronic publication (e-pub) is an electronic file of a publication

An electronic reader (e-reader) is a handheld electronic device that is used to
display an electronic publication (e-pub).

Emerging technology is a technology that is new or cutting edge; it is emerging
in the marketplace.

Innovation is “[a]n idea, practice, or object that is perceived as new by an
individual or other unit of adoption” (Rogers, 2003, p. 474). The newness of an
innovation is relative. It does not have to be a completely new knowledge.
Innovation can include knowledge that is forgotten or known for some time. As
Rogers (2003) states, “If an idea is new to the individual, it is an innovation” (p.
12).

Innovative technology is technology that is innovative or used in an innovative
method.

Learning is “a process of constructing meaning; how people make sense of their
experience” (Merriam & Caffarella, 1999, p. 261).

Public safety professionals are professionals in a broad category that are often
referred to as emergency responders and include: firefighters, police officers,
29
paramedics, emergency managers, and others that are often sent into ill-defined
crisis situations with the expectation that they will solve the complex and
overlapping problems created by a crisis (Ford & Schmidt, 2000).

Simulation is “a production of visual images of objectives and scenes, usually
under real-time conditions, when the original object or scene is not available”
(Welford, 1977, p. 784).

Training is a deliberate and planned effort to develop an employee’s knowledge,
skills, and abilities to do a specific job (Noe, 2003).
Organization of the Dissertation
This dissertation contains five chapters. Chapter I introduces the topic, identifies
the problem, describes the significance of the study, and presents the conceptual and
theoretical frameworks for the study. Chapter II explicates the context for the study
(public safety training) and reviews extant literature relevant to the research topic,
including technology acceptance, change, and digital personality theories that informed
this study: Venkatesh, et al.’s (2003) UTAUT, Lewin’s (1997, 1952) change theory,
Schein’s (1996) adaptation of Lewin’s change theory, Rogers’s (2003) diffusion of
innovations, and Carlson’s (1995) channel expansion theory. Chapter III describes the
research methodology used for the study, including the research design, participant
selection, data collection, and data analysis procedures. Chapter IV reports the findings
of the study. Chapter V discusses significant findings in relation to extant literature,
draws conclusions based on the findings, and offers recommendations for future practice
and research.
30
CHAPTER II
REVIEW OF LITERATURE
The purpose of this chapter is to provide a preliminary review of the literature
related to public safety professionals’ use of innovative technology in a training context.
This chapter is organized into four sections. The first section describes the public safety
training that serves as the context for this study. The second section provides an
overview of the literature concerning technology acceptance. The third section offers a
review of change literature to provide the theoretical frameworks for this study from five
perspectives: Schein’s interpretation of Lewin’s change theory as it relates to learning,
Rogers’s diffusion of innovations, and Carlson’s channel expansion theory (see Figure
1). The fourth section reviews literature concerning the digital personalities of
individuals. Figure 1 is a graphic representation of the theoretical influences to this
study. As it shows, each theory discussed in this chapter, as weighed over the context of
public safety training, contributed to the purpose of this study.
31
Figure 1. Theoretical
framework for the study
Public Safety Training
This section discusses the context of this study: public safety training. The
section begins with a definition of training and follows with a discussion of who public
safety professionals are. It concludes with the performance levels and a discussion of
the content of public safety training.
Training
The literature is rife with discussions and debates that attempt to differentiate
between training and education (Merriam & Caffarella, 1999; This & Lippitt, 1979).
Nevertheless, training, at its core, is a learning opportunity. Training, through planned
learning opportunities, allows for the identification, assessment, and development of the
32
individuals to perform a current or future job (Fitzgerald, 1992; McLagan, 1989; Noe,
2003). The implication from this definition is that trainees “are to master knowledge or
skills and apply these skills to everyday activities” (Stabile & Ritchie, 2013, p. 73).
J. R. Davis and Davis (1998) provide this explanation to help better understand
training:
Training is necessary to help workers qualify for a job, do the job, or advance,
but it is also essential for enhancing and transforming the job, so that the job
actually adds value to the enterprise. Training facilitates learning, but learning is
not only a formal activity designed and encouraged by specially prepared trainers
to generate specific performance improvements. Learning is also a more
universal activity, designed to increase capability and capacity and is facilitated
formally and informally by many types of people at different levels of the
organization. Training should always hold forth the promise of maximizing
learning. (p. 44)
Training is an essential activity to keeping any organization competitive.
Developing the workforce of an organization provides obvious benefits that result in
improved efficiency. Given the challenges that companies and organizations face, they
cannot afford to ignore the benefits that training offers. Yet, Salas, Tannenbaum,
Kraiger, and Smith-Jentsch (2012) provide an eloquent description of the changing
landscape faced by corporations and governments:
…a few common trends include dealing with an aging and, in many cases,
crosscultural workforce; the retraining of displaced personnel; a new generation
33
entering the workforce with different motivations, expectations, and approaches
to learning; access to rapidly emerging technologies that can accelerate or
distract from employee development; and the need to develop an adaptive,
flexible workforce that can adjust to changes, while simultaneously ensuring that
employees have the specific skills they need to do today’s work. (p. 75)
Training is the process of properly and effectively equipping individuals to
perform their jobs, whether current or future. Both planned (Fitzgerald, 1992; McLagan,
1989; Salas et al., 2012; This & Lippitt, 1979) and/or unplanned (Marsick & Watkins,
1997) learning efforts can be used to accomplish training and involve work-related or
more general knowledge that can later be applied to a new job. Salas et al. (2012)
suggest that “the goal of training is to create sustainable changes in behavior and
cognition so that individuals possess the competencies they need to perform a job” (p.
77). Competencies are used to define performance in terms of knowledge, skills, and
attitudes and are measured in small increments for training purposes (Chandler, Qureshi,
Gebbie, & Morse, 2008). Training and development can also be a short duration
activity, but may include life-long learning activities. Training has been used to increase
performance and accuracy in high-risk settings, such as the ones faced by emergency
responders (Salas et al., 2012).
Channing R. Dooley is credited with making the distinction between training and
education that began to emerge in the 20th century He suggested that education was
used to prepare one for life with broad and general knowledge, while training was
specific, typically tied to solving production problems and acquiring skills (Dooley,
34
1945). Since the mid-1940s, training has manifested itself in companies through
corporate employee training programs, as well as federal and state training programs.
Training has been elevated from being a luxury to being an essential strategy to ensure
that companies maintain their competitive edge (McLagan, 1989; Noe, 2003). Despite
the advancements in training, research and theoretical development lagged far behind
other areas up through the 1990s (Kraiger, Ford, & Salas, 1993).
Nationally, the training industry is a $135 billion dollar industry (Salas et al.,
2012). The training field continues to grow, becoming more sophisticated (Salas &
Cannon-Bowers, 2001). Specifically, in fiscal year 2012, the United States Congress
budgeted more than $521 million for the Federal Emergency Management Agency
(FEMA) dedicated to training emergency responders. This amount equates to
approximately 1.15% of the entire U.S. Department of Homeland Security’s (DHS)
annual budget (Appropriations, 2012). This significant investment of financial
resources, time, and effort signifies the importance of training to enhance the capabilities
of public safety professionals in the nation.
Training methods and instructional strategies have grown as well. These
methods and strategies have continually incorporated and integrated innovative
technologies, from the use of overhead projectors in the 1940s and 1950s to the use of
blended learning and computer-supported simulations in the new millennium (Chandler
et al., 2008; Salas & Cannon-Bowers, 2001). Researchers are continually seeking the
best methods and strategies to present training (Salas & Cannon-Bowers, 2001). What is
known about training is that the design, delivery method, and implementation has a
35
major impact on its effectiveness, and when training is properly designed, it works
(Salas et al., 2012).
Public Safety Professionals
Public safety covers a broad category of disciplines concerned with preventing
and mitigating hazards that could endanger the public as well as responding to and
recovering from emergency incidents when they occur. This category includes those
disciplines that are often referred to as emergency responders and includes firefighters,
police officers, paramedics, emergency managers, and others who are often sent into illdefined crisis situations with the expectation that they will solve the complex and
overlapping problems created by a crisis (Ford & Schmidt, 2000). While definitions
abound in the literature, public safety professionals, as emergency responders, are often
defined in general terms as those “who directly respond to a disaster” (Lindell, Prater, &
Perry, 2007, p. 466). In the context of the United States, where this study takes place,
public safety professionals, as emergency responders, are defined by a presidential
directive as:
Those individuals who in the early stages of an incident are responsible for the
protection and preservation of life, property, evidence, and the environment,
including emergency response providers as defined in section 2 of the Homeland
Security Act of 2002 (6 U.S.C. 101), as well as emergency management, public
health, clinical care, public works, and other skilled support personnel (such as
equipment operators) that provide immediate support services during prevention,
response, and recovery operations. (Bush, 2003, p. 2)
36
These professionals represent ten disciplines: fire service, law enforcement,
Emergency Medical Services (EMS), hazardous materials response, public safety
communications, public health, health care, emergency management agency, public
works, and governmental administrative (FEMA, 2013b). Table 1 provides a brief
description of each discipline.
Table 1
Emergency Responder Disciplines and Descriptions
Discipline
Description
Fire service
Provide life safety services including fire suppression,
rescue, arson investigations, public education, and fire
prevention training (FEMA, 2013b)
Law enforcement
Provide law enforcement services intended to deter or
discover criminal activity at the local, state, and federal
levels (Hess & Orthmann, 2012)
EMS
Provide prehospital care and transportation to injured and
ill people
Hazardous materials
response personnel
Public safety
communications
Provide the identification for, assess the risk of, and
mitigate or control the release of hazardous materials
(FEMA, 2013b)
Provide a means to connect persons reporting an incident
and response personnel, as well as a means for responders
to communicate with other response personnel during an
incident (FEMA, 2013b)
Public health
Provide protection against environmental hazards, promote
healthy behaviors, respond to disasters, and ensure the
quality and accessibility of health services (FEMA, 2013b)
Health care
Provide clinical, ancillary, forensic, and administrative
skills in hospitals, clinics, and other facilities offering
medical care (includes medical surveillance, mental health
care, epidemiological investigation, diagnosis, treatment,
and fatality management) (FEMA, 2013b)
37
Table 1
Emergency Responder Disciplines and Descriptions
Emergency
management agency
Provide the application of science, technology, planning
and management at the local, state, and federal levels to
coordinate preparation, recognition, response, and recovery
efforts from large-scale disasters and catastrophes (FEMA,
2013b; Lindell et al., 2007)
Public works
Provide administrative, technical, supervisory, and craft
roles that make up the construction and management of the
nation’s infrastructure (FEMA, 2013b)
Governmental
administration
Consist of elected and appointed officials at the local, state,
and federal levels (FEMA, 2013b).
Each of the disciplines is expected to keep personnel trained for a variety of
emergencies and disasters that may occur within a local community, including those that
could have regional, national, and even international implications and consequences.
This approach, called all-hazards, was initiated after analyses of the preparedness and
response efforts to the 1995 terrorist bombing in Oklahoma City, Oklahoma (G.
Commission, 1999); the September 11, 2001, terrorist attacks (Prieto, 2006); and the
2005 hurricane season (Congress, 2006; Townsend, 2006). As a result of these and other
significant disasters in the United States, the emergency response disciplines underwent
a paradigm change in which they could no longer be stove-piped and must be
interoperable and, in the best sense of the word, interdisciplinary (Bellavita, 2006; The
9/11 Commission, 2004). To reinforce this paradigm of interdisciplinary cooperation,
emergency response teams have been established across the United States. These teams
not only have the obvious capability to respond to a disaster, but they typically have
38
training and exercise capabilities and missions as well (Ford & Schmidt, 2000). Much
of the training used to prepare these public safety professionals is intended to enhance
the knowledge, skills, and abilities of these personnel to be better decision makers
(Klein, 1999; Lindell et al., 2007; Montgomery, Lipschitz, & Brehmer, 2005). To meet
this intent, public safety professionals must “participate in intensive training sessions
and exercises to prepare them for their tasks” (Moats, Chermack, & Dooley, 2008, p.
398). In addition to the new interdisciplinary aspects of emergency response
communities, public safety professionals have seen their roles expanded as the needs of
their constituent communities have evolved in the wake of major disasters (Chandler et
al., 2008).
Types of Public Safety Training
The DHS funding is used to provide public safety professionals a wide variety of
training. Therefore, it is useful to understand how emergency response training has
evolved. For many decades, emergency responder training was accomplished by way of
on-the-job training. Some departments developed recruit academies and organized
training divisions, but standardized training on a national level was largely absent until
the mid-1990s. In the aftermath of the 1995 bombing, the events of September 11, 2001,
and Hurricane Katrina, much of the training for public safety professionals provided by
the Federal Government was reorganized under an organization within DHS called the
National Training and Exercise Directorate (NTED) (FEMA, 2013b). The mission of
the NTED is:
39
to make high-quality training available to the first responder community, tailored
to enhance the capacity of states and local jurisdictions to prepare for, prevent,
deter, and respond and recover safely and effectively from potential manmade
and natural catastrophic events, including terrorism. (FEMA, 2013b, p. xi)
The underlying current of this organization is to make standardized training
available to emergency response organizations at various levels of performance. The
levels of training include awareness-level training, which is designed for those public
safety professionals who will only “recognize and report a potential catastrophic
incident” (FEMA, 2013a). Performance-level training is intended to prepare those
public safety professionals “who perform tasks during the initial response to a
catastrophic event” (FEMA, 2013a). The third performance level of training,
management and planning, is intended to prepare those public safety professionals with
the highest level of responsibility in an incident response. These personnel typically
“build plans and coordinate the response to a mass consequence, manmade, or natural
event” (FEMA, 2013a).
Technology Used in Public Safety Training
The paradigm of modern training is quickly dissolving. Technology (Alexander,
2009; Friedman, 2005; Kirriemuir, 2008; Salmon, 2009) and the learning styles and
preferences of the emerging workforce are rapidly changing around the world (Palfrey &
Gasser, 2008; Prensky, 2001a, 2001b, 2001c; Smart et al., 2007; Tapscott, 2009).
Despite the emphasis on training, there is little evidence to suggest that training
organizations are adapting course designs to address these changes (Oblinger, 2003;
40
Prensky, 2006), especially those organizations that train emergency services workers
(Junginger, 2008). Although the training design is not changing, the technology used in
training public safety professionals is diverse. For the purposes of this study, I have
focused on two technologies that are used in training: (a) e-readers and e-pubs and (b)
simulations.
Electronic readers (e-reader) and electronic publications (e-pub). An ereader is a handheld electronic device used to display an e-pub. While there are several
e-readers on the market, the e-readers share common features, including the ability to
display and navigate through e-pubs. Many e-readers are multifunction tablet-like
computers that have capabilities to navigate the Internet. For example, the iPad, which
is used in one of the two courses in this study, has the ability to run apps, or
individualized computer programs that typically use the Internet 2.0.
E-pubs are, as the name implies, an electronic file that contains a publication.
These file formats are often proprietary in nature and do not conform to a single
standard. While there is an emerging standardized format created by the International
Digital Publishing Forum (IDPF), most e-readers are not able to read competitor’s
formats (Dougherty, 2010).
E-pubs and e-readers are becoming popular with training organizations and
managers because they reduce the cost of training by allowing rapid changing to training
materials and eliminating the cost of printing manuals. Some training participants enjoy
these e-readers and e-pubs because it allows for greater portability of the course
materials. Another of the benefits of an e-reader is that it is capable of carrying multiple
41
e-pubs, in many case thousands. If these thousands of publications were carried in hard
copy format, they would completely fill a small library and weigh several tons.
Simulations. For the purposes of this study, a simulation is “a production of
visual images of objectives and scenes, usually under real-time conditions, when the
original object or scene is not available” (Welford, 1977, p. 784). The fidelity, or ability
of the simulation to accurately reproduce the effect, ranges from low to high; in other
words, the higher the fidelity of the simulation, the more accurately the simulation
portrays the original object.
Public safety training uses a wide variety of simulations, ranging from colored
rags to represent smoke and fire, to high fidelity computer-supported simulations such as
E-Semble’s XVR and the Texas A&M Engineering Experimentation Station’s
Emergency Management Exercise System (EM*ES). The situational context that these
simulations provide, regardless of the fidelity, are paramount to the experiential learning
opportunities public safety professional need to develop. These situational contexts
provide public safety professionals the ability to develop decision-making skills in a
myriad of applications, including tactical and strategic management of emergency
situations, leadership, and crisis communications (Crandall, Klein, & Hoffman, 2006;
Klein, 1993, 1997, 1998; Klein & Weitzenfeld, 1979; Zsambok & Klein, 1997).
Technology Acceptance
Technology is ubiquitous in our lives. Although the integration and use of
technology is often intended to make the tasks of life easier and more efficient, it can
also lead to frustration, embarrassment, and even anger. The successful use of
42
technology requires that individuals must at least partially accept technology; however,
in training applications, technology acceptance is not the sole responsibility of the
learner. To be successful, “instructors, curriculum developers, and QA/QC personnel
will all need the skills to design a learning environment that facilitates learning and then
apply different instructional strategies” (McGurn & Prevou, 2012, p. 1533). This section
provides an overview of the literature concerning technology acceptance starting with
Ajzen’s and Fishbein’s (1980) theory of reasoned action and then progresses to the
technology acceptance model that stemmed from Davis’s (1986) doctoral dissertation.
This review culminates in a review of UTAUT.
As I explained in Chapter I, technology acceptance is the individual’s decision to
embrace technology for a given application. Significant research on the concept of
technology acceptance exists in the literature; however, there are two important gaps.
First, there are few, if any, studies that address the acceptance of technology that is used
to facilitate training. Second, the preponderance of the existing literature addresses the
topic from a quantitative perspective, excluding much of the depth and richness of the
phenomena that qualitative studies provide. In this section I will discuss the existing
technology acceptance literature beginning with the Theory of Reasoned Action (TRA)
(Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975) and culminating with UTAUT
(Venkatesh et al., 2003).
Theory of Reasoned Action (TRA)
TRA (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975) provides the backdrop
for the present technology acceptance studies, including the Technology Acceptance
43
Model (TAM) (F. D. Davis, 1986) and UTAUT (Venkatesh et al., 2003). TRA states
that the two typical determinants of an individual’s behavioral intention are attitude and
the subjective norm (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975; Y.-H. Lee,
Hsieh, & Ma, 2011; Yousafzai, Foxall, & Pallister, 2007). Moreover, TRA suggests that
a person’s stated intention to take an action is the most immediate predictor of that
action (Ajzen & Fishbein, 1980; Hagger, Chatzisrantis, & Biddle, 2002). The theory
also purports that the subjective norm is heavily influenced by the individual’s
perception of those who are important or significant to the decision maker and those
persons’ desire to have the individual participate in the intended behavior (Fishbein &
Ajzen, 1975; Hagger et al., 2002). In other words, TRA suggests that a person’s
decision to act is heavily influenced by the opinions and/or desires of those with
significant influence over him or her.
Technology Acceptance Model (TAM)
The TAM (F. D. Davis, 1986) is the most widely used and studied theory of
technology acceptance (Y.-H. Lee et al., 2011; Y. Lee et al., 2003). The TAM was
created through an adaptation of TRA (Ajzen & Fishbein, 1980; Fishbein & Ajzen,
1975) “to explain computer usage behavior” (F. D. Davis et al., 1989, p. 983). The
TAM connects the dots for “the causal relationship between users’ internal beliefs,
attitude, intentions, and computer usage behavior” (Yousafzai et al., 2007, p. 251). The
results of these connections indicate that technology acceptance is determined through
two primary variables: (a) perceived use and (b) perceived ease of use (F. D. Davis,
1986; F. D. Davis et al., 1989).
44
Since its first publication in 1986, the TAM has been used to explore the
acceptance of numerous technologies, including word processors, communications
systems, office systems, and specialized business systems (Y. Lee et al., 2003; Yen et
al., 2010); wireless technology (Yen et al., 2010); e-learning systems (Y.-H. Lee et al.,
2011); and online communities (Chung, Park, Wang, Fulk, & McLaughlin, 2010). In
addition, researchers have used the TAM to explore the technology acceptance of
students in educational institutions (Jonas & Norman, 2011; Y.-H. Lee et al., 2011; Liu
et al., 2010). According to Yousafzai et al. (2007) “replication of the original TAM
study suggests that it holds across persons, setting, cultures, countries and times” (p.
264).
Existing technology acceptance literature indicates that individuals are most
likely to accept technology when three general criteria are met: (a) the utility of the
technology is understood to help the individual do his or her job better, (b) the outcome
of learning to use the technology is worth the effort, and (c) the individual can see
himself or herself using the technology (F. D. Davis, 1986, 1989; F. D. Davis et al.,
1989; Venkatesh et al., 2003). Ultimately, technology acceptance boils down to an
individual’s decision. Klein (1998) suggests that decisions are based on the individual’s
“use of experience to recognize key patterns that indicate the dynamics of a situation” (p.
31).
The Unified Theory of Acceptance and Use of Technology (UTAUT)
The bulk of research on the predictors of technology acceptance culminates
within UTAUT (Venkatesh et al., 2003). In this seminal study, Venkatesh et al. (2003)
45
performed an empirical comparison of eight models with a combined total of 32 main
effects and four moderators that are identified as determinants of intention and behavior.
These eight models include TRA (F. D. Davis et al., 1989), the TAM (F. D. Davis,
1989), and innovation diffusion theory (Karahanna, Detmar, & Norman, 1999). From
this comparison, researchers identified seven constructs as being a direct determinant of
intention or usage. Additionally, they determined that each of the eight models have a
common, underlying conceptual framework, illustrated in Figure 2.
Figure 2. Basic conceptual framework underlying user acceptance models.
Adapted from “User acceptance of information technology: Toward a unified view,” by
V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, 2003, MIS Quarterly, 27(3),
p. 427.
The authors distilled the seven constructs to four important predictors of
technology acceptance: (a) performance expectancy or “the degree to which an
individual believes using the system will help him or her to attain gains in job
performance” (Venkatesh et al., 2003, p. 447); (b) effort expectancy or “the degree of
ease associated with the use of the system” (Venkatesh et al., 2003, p. 450); (c) social
influence or “the degree to which an individual perceives that important others believe
he or she should use the new system” (Venkatesh et al., 2003, p. 451); and (d)
46
facilitating conditions or “the degree to which an individual believes that an
organizational and technical infrastructure exists to support the use of the system”
(Venkatesh et al., 2003, p. 453). Using these four determinants, the authors then
conducted an empirical validation and cross validation of the theory. Through this, the
authors found considerable support for the theory, claiming that the UTAUT “was able
to account for 70 percent of the variance (adjusted R2) in usage intention.” (Venkatesh et
al., 2003, p. 467).
However, in both the validation and cross-validation of the UTAUT, the focus
was on the application of technology in the performance of an individual’s job, not on
technology used in either training or education applications. Additionally, the
technology in question appears to be a single system (e.g., typically a computer
application or a computer system), not complex technologies (e.g., a simulation).
Moreover, the study predates many of the current innovative technologies and systems
that are ubiquitous in the current setting, including smartphones, e-readers, iPads, and
many current interactive course formats. Finally, the UTAUT does not appear to
validate the antecedents. Simply said, there is little if any verification that the
antecedents accurately predict that individuals accept and use technology. Likewise,
there is no evidence that personal narratives of individuals have been used in any study.
Change
Change is a central theme to this study because trainees who are asked to use
(accept) innovative technology are essentially asked to make a change in how they learn.
Change is described as an important, “profound psychological dynamic process”
47
(Schein, 1996, p. 28). Change is also “such a multifaceted phenomenon that every
attempt is necessarily limited” (Poole, 2004, p. 4). Therefore, the next section of this
chapter discusses three significant areas of change literature: Schein’s (1996)
interpretation of Kurt Lewin’s change theory as it related to the classroom; Rogers’s
(2003) diffusion of innovations; and Carlson’s (1995) channel expansion theory. By
understanding these processes, we are able to better understand the decision-making
processes that facilitate change.
Change Theory in the Field and in the Classroom
Lewin’s (1997, 1952) change model is as simple as it is foundational to much of
the literature on change. Lewin proposes that change occurs in three phases: unfreezing,
transition or move, and refreezing (Lewin, 1997, 1952; Schein, 1996). In unfreezing, the
individual removes restraining forces that would prevent or significantly resist change.
In the second phase, change, new behaviors are developed that shift the individual to a
new level. In refreezing, the individual is stabilized at a new equilibrium, often
supported by the organization, or change agents, and the change is ultimately
institutionalized. Edgar Schein (1996) provides great insight into how his own thinking
has “evolved from theorizing about planned change to thinking about such processes as
managed learning” (p. 27).
Schein (1996) adapts Lewin’s change model to learning because, at its origin,
learning is simply a change. While the three basic steps of the change process remain
the same, Schein suggests that as individuals work through each of the steps, there are
multiple events they must work through. Specifically, as individuals work through the
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process of unfreezing, they initially experience a period of disconfirmation.
Disconfirmation is characterized as a “dissatisfaction or frustration generated by data”
(Schein, 1996, p. 29) that calls the previously known truth into question. While the
sources of disconfirmation vary, they are a driving force signaling the need for change.
To progress through the unfreezing process, individuals must recognize and “accept the
disconfirming data as valid and relevant” (Schein, 1996, p. 29).
However, accepting these data often sets up an internal conflict that typically
results in a defensive reaction, or what Schein (1996) calls a “learning anxiety” (p. 29).
Schein describes anxiety as “the fundamental restraining force which can go up in direct
proportion to the amount of disconfirmation” (p. 29) that will often lead to a denial of
the data that challenges the current belief. In other words, this anxiety triggers a
psychological defense mechanism that denies the data that initially signaled the need for
change. This defensive reaction, initiated to avoid the potential pain created by the
perception of a loss of effectiveness, self-esteem, or even the individual’s identity, must
be overcome to move forward through the change process. Either the individual must
overcome the learning anxiety or establish a psychological safety mechanism.
The next step of the change process, changing or transitioning, begins with what
Schein (1996) called “cognitive redefinition” (p. 30). This three-step sub-process begins
with a semantic redefinition where words take on a new meaning; progresses through a
cognitive broadening in which a concept is expanded beyond what was once thought;
and terminates with a shift in the scale of judgment or, in essence, the standards of
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judgment and evaluation are redefined (Schein, 1996). These steps can only occur when
the learner has “opened him- or herself up to new information” (Schein, 1996, p. 31).
As Schein (1996) wrote, “If one is motivated to change…one may be able to
‘hear’ or ‘see’ something from a new perspective” (p. 31). Schein points out, that the
learner’s motivation to change is an important factor in the efficacy of role models. This
process is often facilitated through a conversational process with someone else (Schein,
1996). The role of others’ influence is discussed in greater detail later in this chapter as
“opinion leaders” (Rogers, 2003, p. 308) and “change agents” (p. 366). Regardless,
Schein makes it clear that it is important to have a well-prepared role model. Schein
(1996) cautions:
to rely on identification with a role model, that explains why so many
consultation processes go awry. The consultant, by design or unwittingly,
becomes a role model and generates solutions and cognitive categories that do
not really fit into the culture of the client organization and will therefore be
adopted only temporarily. (p. 33)
Once the change has occurred, refreezing occurs. Schein cautions leaners to be
aware of the congruency between the new behavior and the rest of the learner’s
behaviors and personality. If there is too much of a gap between the learned behavior
and the remaining behaviors, it is likely that the new behavior will be unlearned.
Second, it is important to let the learner identify solutions that fit him or her. Therefore,
if a role model is used, he or she must not provide solutions. Instead, he or she must
coach the learner to identify the solution that best fits that learner. Finally, Schein
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(1996) concludes when dealing with changing whole groups, “it is best to train the entire
group that holds the norms that support the old behavior” (p. 34). Schein’s (1996) essay
showed that Lewin’s model is adaptable to a learning paradigm. More importantly, his
essay has expanded and enriched the understanding of change theory.
Diffusion of Innovations
Processes describing how innovation is communicated to members of a social
system over time are applicable to this study. Perhaps the most well-known model for
this is detailed in Rogers’s (2003) monograph. Diffusion of innovations focuses on a
process of how individuals accept innovation. Rogers (2003) outlines four main
elements of diffusion: (1) an innovation, (2) communication through certain channels,
(3) time, and (4) a social system.
As defined in Chapter I, innovation is “an idea, practice, or object that is
perceived as new by an individual or other unit of adoption” (Rogers, 2003, p. 12).
Innovation is not limited to tangible products such as computers or technologies;
innovation also includes ideas and concepts. Moreover, these products and ideas do not
need to be emerging or cutting edge to be innovative. By Rogers’s definition, if the
implementation or utilization of the product or idea is new to the user, it would be
considered innovative. Therefore, what is considered innovative is more about exposure
than the relative age of the product or concept.
Understanding how an innovation is communicated among participants is
significant to understanding how the technology is accepted given the social
constructivist nature of technology acceptance. We must first understand that
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communication, as it pertains to the diffusion of an innovation, is a process in which
information is created and shared among participants to gain a mutual understanding
(Rogers, 2003). However, Rogers (2003) suggests that a potential challenge to the
communication of an innovation is that participant groups are, by and large,
heterophilous, meaning that participants have differing critical attributes. This has an
impact on how participants select communication channels and ultimately whether they
accept the innovation. Later in this chapter, Carlson’s (1995) channel expansion theory
is used to describe how individuals choose communication channels.
Time is the third element of the diffusion process. Rogers (2003) provides three
dimensions in which time comes into play: (a) an innovation’s rate of adoption within
the system, (b) the innovativeness of an individual or other unit of adoption, and (c) the
innovation-decision process.
The rate of adoption refers to “the relative speed with which an innovation is
adopted by members of a social system” (Rogers, 2003, p. 23). Rogers explains that the
typical rate of adoption can be illustrated as an S-curve because only a few people,
referred to as early adopters or innovators, adopt the innovation. As more people adopt
the innovation, the diffusion curve climbs. Eventually, the rate of adoption will level off
and then begin to decline as there are fewer people left to adopt the innovation.
Eventually, the process of diffusion completes the S-curve (Rogers, 2003).
The innovativeness of an individual refers to the relative time in which an
individual adopts new ideas compared to another member within the system (Rogers,
2003). Rogers provides several categories to describe the continuum of innovativeness
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ranging from innovators and early adopters to the late majority and laggards. The
determination of one’s position on the continuum is based on the relative time in which
the individual adopts an innovation compared to the whole time for diffusion. This
relativity is important because diffusion times will always vary greatly.
While each of these time dimensions has implications for this study, the most
significant is the innovation-decision process. This process outlines how an innovation
is adopted (or rejected) over time. The process begins with gaining an initial knowledge
of an innovation, through a decision to adopt (or reject) the innovation, and then to
confirmation of the decision. This process is applicable to any unit of adoption from the
individual, to the organization, or even to a society. Figure 3 provides an illustration of
the process.
Figure 3. A model of five stages in the innovation-decision process.
Recreated from Rogers (2003). Diffusion of innovations (5th ed.). New York: Free Press., p. 170.
53
There are empirical studies that validate the stages of the innovation-decision
process. One such study is a 1960 study of Iowa farmers conducted by Beal and Rogers
(as cited in Rogers, 2003). Another study examined the process used by teachers in
California. Given these and other studies cited, Rogers asserts that stages do exist in the
process.
As Figure 3 shows, Rogers (2003) presents a five-stage process that is
“essentially an information-seeking and information processing activity” (p. 172). The
process begins when an individual is exposed to the innovation and gains some
understanding of how it functions. There are three types of knowledge that are
important to this stage: (a) awareness knowledge, or the basic information that alerts the
individual that the innovation exists; (b) how-to knowledge, or information needed to
properly use the innovation; and (c) principles knowledge, or information explaining the
principles that underlie how the innovation works (i.e., the theory of the innovation).
The three types of information provide the what, how, and why basics of the innovation
(Rogers, 2003).
The persuasion stage occurs as the decision maker formulates an opinion of the
innovation, either favorable or unfavorable. This stage signifies a change in the probable
decision maker. First, during this stage, as Rogers (2003) writes, “the individual
becomes more psychologically involved with the innovation” (p. 175). The individual
also interprets, verifies, and validates the information gained in the first stage and begins
an evaluation of the innovation. This is all in a concerted effort to form an opinion about
the innovation.
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In the third stage of this process, the individual makes a decision to adopt or
reject the innovation. Adoption is defined as the “decision to make full use of the
innovation as the best course of action available” (Rogers, 2003, p. 177) and rejection is
defined as “a decision not to adopt the innovation” (p. 177). According to Rogers, the
decision maker will often try out the innovation on a partial basis. This auditioning of
the innovation is an important activity for adoption. Rogers (2003) observes that “most
individuals do not adopt an innovation without first trying it on a probationary basis to
determine its usefulness in their own situation…Innovations that can be divided for trial
are generally adopted more rapidly” (p. 177). While this stage is generally when the
decision to adopt or reject is made, it is important to note that any stage is a potential
rejection point.
If the decision to adopt is made, the process moves forward to the next stage:
implementation. Usually, this stage immediately follows the decision stage, unless
logistical issue prevent an immediate implementation (Rogers, 2003). The logistics of
implementation can be exacerbated when an organization is the implementer as opposed
to an individual. Up to this point, the innovation-decision process has largely been a
mental exercise; during this stage, steps are taken to put the innovation to use. In the
final stage, confirmation, the decision maker seeks support for the decision he or she
made. It is important to note that the decision maker can reverse the decision, or
discontinue using the innovation, if support cannot be garnered or if conflicting
messages about the innovation arise. This stage usually closes when the innovation is
institutionalized (Rogers, 2003).
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Rogers (2003) reports that several studies indicate that the decision to adopt and
the subsequent implementation are not the termination of the process. Therefore, the
confirmation stage is an important part of many decision processes. During this stage,
the decision maker seeks reinforcement for the already-made decision and “seeks to
avoid any dissonance or reduce it if it occurs” (Rogers, 2003, p. 189). If the decision
maker cannot reduce dissonance or find support for the innovation, discontinuance is
likely to occur. There are two types of discontinuance: replacement and disenchantment.
Replacement discontinuance is a decision to discontinue using an innovation to make
way to adopt a better innovation. Disenchantment discontinuance is the decision to
discontinue the use of an innovation due to dissatisfaction with its performance to meet
the user’s needs.
At its root, Rogers’s (2003) diffusion is social change. Diffusion cannot take
place without a change in the “structure and function of the social system” (p. 6). Social
networks and interpersonal communications that are capable of sharing information
about the innovation greatly influence the decision to adopt or reject an innovation. The
opinion leader and the change agent are important facilitators of this change and the
adoption or rejection of the innovation.
Opinion leaders and change agents. As stated earlier in this chapter, most
diffusion groups are heterophilous. Rogers (2003) observed that when these
interpersonal diffusion networks are heterophilous, the followers seek the opinion of the
opinion leaders. These opinion leaders typically have better qualifications than the
followers. These qualifications include a better education, more exposure to the mass
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media, more exposure to the world (i.e., better traveled), more contact with change
agents, and more innovation (Rogers, 2003). Given these qualifications, the opinion
leaders are “perceived as more technically competent” (Rogers, 2003, p. 308) about the
innovation and consequently are able to influence others. As the leaders’ influence takes
hold, the followers’ use of the innovation increases and consequently begins to impact
the aforementioned S-curve. The influence of the opinion leader is also supported in the
literature. Rogers cites 10 studies that provide support to the influencing power of the
opinion leader; however, keeping the opinion leader current and trained is an essential
part of maintaining his or her influence. This activity cannot be neglected.
A change agent is “an individual who influences clients’ innovation-decisions in
a direction deemed desirable by a change agency” (Rogers, 2003, p. 366). The role of
the change agent is to close the deal on the adoption of the innovation and slow or stop
the adoption of innovations with undesirable effects. Change agents typically operate by
employing one or more of the following seven strategies: (a) developing a need for
change, (b) establishing an information exchange relationship between individuals, (c)
diagnosing problems, (d) creating an intent to change in the client, (e) translating intent
to action, (f) stabilizing the adoption and preventing discontinuance, and (g) achieving a
terminal relationship (Rogers, 2003).
Channel Expansion Theory
Channel expansion theory (Carlson, 1995) emerged in response to the
inconsistent empirical support within the literature concerning media richness theory
(Carlson, 1995; Carlson & Zmud, 1999). Media richness theory (Daft & Lengel, 1984)
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suggests that communication channels within an organization have certain characteristics
that limit or enhance their ability to carry messages, making richer channels “more
suited to carrying equivocal messages than other less rich channels…” (Carlson, 1995,
pp. 4-5). A channel is a medium of communication and is considered richest when it
provides rapid feedback, multiple cues, specifically tailored messages, and subtleties
through natural language. Therefore, the richest channels provide participants (i.e.,
sender and receiver) the greatest opportunity to reduce the ambiguity of the message.
Channels range from face-to-face communication on the richest end to formal numeric
language on the least rich, or lean, end. Face-to-face communication is designated as the
richest channel because of the ability for immediate feedback and the myriad of clues
that can be transmitted and received, whether verbal, nonverbal, visual, etcetera.
Moreover, face-to-face communication allows the message to be customized to the
specific receiver and, because it requires the use of a natural language, it is able to
convey the aforementioned subtleties. In contrast, binary text, the ones and zeros of
computers, is considered to be the least rich because it is in no way interactive, is not
able to be tailored to the recipient, and is not a natural language. It therefore provides no
opportunity for feedback (Carlson, 1995; Daft & Lengel, 1984).
However, as Carlson (1995) and Carlson and Zmud (1999) explain, media
richness theory was not consistently supported by empirical research. Because of these
inconsistencies, Carlson conceptualized channel expansion theory. This theory explains
these inconsistencies by describing media richness as “a perception of the user which is
based on experience and familiarity with the medium, experience and knowledge
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concerning the message topic, experience working in the present organizational context,
as well as the nature of the user’s relationships with each communication ‘coparticipant’” (Carlson, 1995, pp. 1-2). Channel expansion theory also explains how
users are able to expand the richness of a channel to better accommodate the delivery of
a specific message. They are able to exploit the channel’s capabilities by becoming
“more familiar with the channel-in-use” (Carlson, 1995, p. 2). This would suggest that
the more experience a person has with the given channel and with the subject matter, the
more likely the person would be to find the channel richer than other people with less
experience would. In other words, the richer the channel (i.e., the technology), the more
likely the individual is to accept the technology in a training application.
Digital Personalities: The Immigrants, Natives, and Settlers
Much has been written concerning the differences in people’s adaptability and
use of technology. Prensky (2001b) brought this discussion to the forefront by
identifying the characteristics of digital natives and digital immigrants. Prensky (2001b)
describes digital immigrants as, “Those of us who were not born into the digital world
but have, at some later point in our lives, become fascinated by and adopted many or
most aspects of the new technology” (p. 1). Prensky (2001b) described digital natives as
“native speakers of the digital language” (p. 1). He suggests that the digital natives are
very different from the other users of digital technologies because they “develop
hypertext minds. They jump around. It’s as though their cognitive structures were
parallel, not sequential…We now have a new generation with a very different blend of
cognitive skills than its predecessors” Prensky (2001c, p. 4).
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Palfrey and Gasser (2008) advanced the conversation by identifying three distinct
digital personalities: digital immigrants, digital settlers, and digital natives. For the
purposes of this study, a digital personality refers to an individual’s attitudes, interests,
social roles, and other traits that relate to his or her use of technology. According to
Palfrey and Gasser (2008), a digital immigrant is described as a hesitant adopter of
technology, while the digital settler uses technology but still relies heavily on other
analog forms of interaction. In contrast, digital natives have access and possess strong
technology-use skills. Moreover, natives share a common culture that is strongly
influenced by their exposure and interactions with technologies, their culture, people
outside of the culture, and institutions.
Many suggest that the digital personality is inextricably tied to the era in which a
person was born (Prensky, 2001b, 2006; Strauss & Howe, 1991; Tapscott, 2009). It is
further suggested that the key to understanding trainees’ experiences with technology is
gaining an understanding of their digital personality (Tapscott, 2009). However, there is
little empirical evidence to support the digital personality paradigm. Bennett, Maton,
and Kervin (2008) define the conundrum:
The debate over digital natives is thus based on two key claims: (1) that a distinct
generation of ‘digital natives’ exists; and (2) that education must fundamentally
change to meet the needs of these ‘digital natives’. These in turn are based on
fundamental assumptions with weak empirical and theoretical foundations. (p.
777)
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In their exploration of the issue, (Bennett et al., 2008) challenge the assertions of
Palfrey and Gasser, Prensky, and Tapscott through presenting recent empirical studies.
For example, Bennett et al. (2008) present evidence showing that the claims of high
technology skills among digital natives are overstated. As they conclude their article,
the authors issue a call for research on the issue of digital personalities:
The time has come for a considered and disinterested examination of the
assumptions underpinning claims about digital natives such that researchable
issues can be identified and dispassionately investigated…It is to call for
considered and rigorous investigation that includes the perspectives of young
people and their teachers, and genuinely seeks to understand the situation before
proclaiming the need for widespread change. (p. 784)
Chapter Summary
The purpose of this chapter was to provide a preliminary review of the literature
related to public safety professionals’ use of innovative technology used in a public
safety training context. This chapter was organized into four sections. The first section
described the context for this study: emergency response training. The second section
provided an overview of the literature concerning technology acceptance. The third
section provided a review of change literature to provide the theoretical frameworks of
this study from five perspectives: Schein’s interpretation of Lewin’s change theory as it
relates to the classroom, Rogers’s diffusion of innovations, and Carlson’s channel
expansion theory. The fourth section reviewed literature concerning the digital
personalities of individuals.
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CHAPTER III
METHODOLOGY
Schwandt (2001) defines methodology as a “social science discourse that
occupies a middle ground between discussions of method and discussions of issues” (p.
161) that “involves analysis of the assumptions, principles, and procedures in a
particular approach to inquiry” (p. 161). In this chapter, I address the methodological
issues related to this study. I begin the chapter with a restatement of the research
purpose and question. I then provide the research paradigm for the study, including the
justification for and description of the qualitative methodology (hermeneutic
phenomenology); descriptions of the research setting, population, and sampling
techniques I employed; as well as data collection and analysis methods. I conclude the
chapter with an acknowledgement of my biases as a researcher and the strategies
employed to ensure the trustworthiness of the study.
Restatement of the Purpose and Research Question
In this study, I explored the experiences of public safety professionals to better
understand their experiences as they use innovative technology in a public safety
training context. Studying this topic is significant for two reasons. First, little research
was available on the phenomenon of individuals’ experience using innovative
technology from an interpretivist perspective. The preponderance of available literature
is focused on assessing the determinants of an individual’s willingness to accept
technology (Y.-H. Lee et al., 2011; Y. Lee et al., 2003; Yousafzai et al., 2007). Second,
the implications and conclusions from this study can aid practitioners in better
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incorporating innovative technologies into training. Ultimately, my aim in this study
was at filling the gaps of knowledge concerning the phenomenon of using innovative
technology used to facilitate training.
I designed this study to address this issue by exploring the lived experiences of
public safety professional who used innovative technologies in a public safety training
context. I used the following research question to guide the study: What are the
experiences of public safety trainees who are required to use innovative or emerging
technology in face-to-face training?
Research Paradigm
My goal in conducting this study was to understand the phenomenon of
individuals’ experiences using innovative technology in a training context. This goal fits
with the philosophy and intent of the interpretivist paradigm. The interpretivist
paradigm is based on “the epistemology of idealism…and encompasses a number of
research approaches, which have a central goal of seeking to interpret the social world”
(Ajjawi & Higgs, 2007, p. 613). I chose a qualitative approach for this study because I
sought to make meaning of the individuals’ lived experience as they encountered the
technology. I also chose this approach because there are many perspectives, perhaps
better described as realities, of technology acceptance.
Qualitative research is often used when there is a need to “understand and
explain the meaning of social phenomena with as little disruption of the natural setting
as possible” (Merriam, 1998, p. 5). Denzin and Lincoln (2005) define this approach as
“a situated activity that locates the observer in the world…[that] involves an interpretive,
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naturalistic approach to the world” (p. 3). In contrast to the positivist paradigm, a
naturalistic inquiry allows for, and in fact assumes, multiple realities and asserts that no
amount of rational process or increased data can resolve the differences between them
(Ajjawi & Higgs, 2007; Erlandson, Harris, Skipper, & Allen, 1993).
A key assumption I held throughout this process was that meaning is constructed
as people interact with their social worlds. Much like jazz, constructing meaning is an
improvisation, a process of intertwining melodies, harmonies, and a beat to create an
entirely new composition (Denzin & Lincoln, 2005). To create this new composition, I
used a wide variety of empirical materials, including personal experience, introspection,
interview, and artifacts. I took these data and laced them together to make sense of the
phenomenon as it occurs in the world. More importantly, as I did this, I examined the
composition as a whole, because it cannot be decomposed and examined as pieces and
parts. To isolate any part from the whole context would severely and irreparably
degrade the meaning (Erlandson et al., 1993).
Social Constructivism
As I prepared for conducting this study, I undertook a long period of reflection to
identify my ontological and epistemological position. Throughout this reflection, I
became acutely aware that meaning and understanding—in other words, reality—is
subjective and constructed through the interactions within the world. Therefore, I
conducted this research through a lens of social constructivism (Crotty, 1998). Social
constructivism suggests that realities, whether social, political, or even psychological,
are socially constructed (Creswell, 2007; Crotty, 1998; Patton, 2002). The research
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question demonstrated this ontological and epistemological worldview with the focus on
the lived experience of the individuals. In this worldview, meaning is not created, but
constructed from the pieces of data that exist in the world (Crotty, 1998).
Rationale for a Phenomenological Approach
Dooley and Lynham (2003) argued, “[Human Resource Development (HRD)]
needs to understand the meaning of lived experiences in organizations, what it means to
be a ‘human resource’ [sic] in the context of an organization, and it needs to do so in a
deeply respectful way” (p. 231). They further noted, “the purpose of interpretive science
is to make sense of, to understand text, be the latter of written, verbal or active form, and
to expose hidden meaning” (Dooley & Lynham, 2003, p. 229). In these two statements,
Dooley and Lynham provide an important nexus of the field of HRD and the
interpretivist paradigm.
A number of approaches that can be invoked to conduct a qualitative inquiry,
include grounded theory, narrative research, ethnography, case study, and
phenomenology (Creswell, 2007). I used a phenomenological approach to explore the
lived experience of public safety professionals as they encountered innovative
technologies in a training context. Van Manen (1990) stated, “The aim of
phenomenology is to transform lived experience into a textual expression of its
essence…a notion by which the reader is powerfully animated in his or her own lived
experience” (p. 36). The lived experience is the basis of phenomenological research
(Groenewald, 2004; Moustakas, 1994; Patton, 2002; van Manen, 1990) and refers to an
individual’s immediate, unvarnished, and natural awareness of life (van Manen, 1990).
65
More importantly, the lived experience is “something of the past that can never be
grasped in its full richness and depth” (van Manen, 1990, p. 36). This naturalistic
ontological perspective is precisely why qualitative researchers are called to conduct
research in the natural setting.
Creswell (2002) suggests three considerations for determining an approach to a
research study: (a) fitting the approach to the audience, (b) relating the researcher’s
experiences to an approach, and (c) matching the approach to the research problem.
After mulling these considerations, I determined that a qualitative approach was the most
appropriate. Specifically, a hermeneutic phenomenological approach is the best to gain
a greater understanding of the individuals’ experience of encountering innovative
technology (Creswell, 2002; Groenewald, 2004; Marshall & Rossman, 1999; van
Manen, 1990).
In addition to Creswell’s (2002) considerations and after a thorough review of
the literature on the topic of technology acceptance, it became clear that the vast
majority of research was conducted from a positivist perspective. There was little
research using an interpretivist lens on the subject of technology acceptance. It is
notable that the aforementioned connection made by Dooley and Lynham (2003) is
deepened by asserting that to improve performance, one must first understand the current
system and status quo. Without this understanding, change and its outcomes are not
recognizable. They discovered that “developing deep understanding of phenomena
within human organizations is imperative in building sound theory and practice in HRD”
(Dooley & Lynham, 2003, p. 232). Therefore, I felt that by understanding individuals’
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lived experience as they encounter innovative technology, it is possible to lay the
groundwork to improve performance. These factors led me to choose a hermeneutic
phenomenological methodology for this study.
Methodology: The Hermeneutic Phenomenological Approach
Phenomenology is an interpretivist, qualitative approach used in the social
sciences based largely on the philosophies of Kant, Hegel, Husserl, and Schutz
(Groenewald, 2004; Patton, 2002). More recently, social scientists such as Max van
Manen (1990) and Clark Moustakas (1994) have built on those early foundations with
the intent of returning to the concrete (Groenewald, 2004; Patton, 2002).
Phenomenologists are concerned with gaining a deep understanding of a phenomenon
from the perspectives of those who have experienced it. Patton (2002) notes,
“Phenomenologists focus on how we put together the phenomena we experience in such
a way as to make sense of the world, and, in doing so, develop a worldview” (p. 69).
Hermeneutic phenomenology is an integration of phenomenology and
hermeneutics, the “philosophy of interpreting the meaning of an object” (Schwandt,
2001, p. 115), and provides the underpinning of the methodology employed throughout
this study (Ajjawi & Higgs, 2007; van Manen, 1990). Smith (1983) writes that this is “a
research methodology aimed at producing rich textual descriptions of the experiencing
of selected phenomena in a lifeworld of individuals that are able to connect with the
experience of all of us collectively” (p. 80).
The lived experience is reflexive and can never be fully captured. Therefore, a
reflective approach provides the best path for the researcher to arrive at a fuller
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understanding (essence) of the phenomenon (Creswell, 2007; Moustakas, 1994; van
Manen, 1990). The hermeneutic phenomenology, as described by van Manen (1990),
allows the researcher to explore the lived experience of individuals by interpreting the
meaning of the lived experiences (Creswell, 2007).
This in-depth exploration occurs through the dynamic interplay of six distinct
research activities: (a) addressing a phenomenon that interests the researcher, (b)
investigating the lived experience not as it is conceptualized, (c) reflecting on the
essential themes that characterize the nature of the phenomenon, (d) describing the
phenomenon through writing and then re-writing, (e) maintaining a strong and focused
relation toward the phenomenon, and (f) balancing the research context by considering
the parts and whole (Creswell, 2007; van Manen, 1990).
Hermeneutical phenomenology uses the person-to-person interview as a primary
method. This method is critically important because of the specific purpose it serves in
eliciting descriptions of the lived experiences from the participants (Patton, 2002; van
Manen, 1990). The interview is used to explore and gather experiential narrative
materials; it may also be used as a vehicle to develop a relationship with an interviewee
(van Manen, 1990). Kahn and Cannell, (as cited in Marshall & Rossman, 1999),
describe the interview as “a conversation with a purpose” (p. 108). Therefore, I
carefully chose interview questions to elicit the responses that focused on the
phenomenon. Equally important, I took extreme care during the interviews to let the
participants’ narrative of the experience unfold from their perspective instead of how I
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thought it should (Marshall & Rossman, 1999). Consequently, the interviews were not
rigidly structured to place the method above the question.
The basis of this study was rooted in a practical problem of understanding how
individuals react to and cope with encountering innovative technology in a training
context. Throughout the research process, I focused and reflected on essential themes to
better understand the lived experience of individuals as they deal with the challenges and
promises of innovative uses of technology training applications (Creswell, 2007).
Methods
This section describes the methods I used when conducting and reporting this
phenomenological research study. My methods include sampling, data collection, and
data analysis. All of these methods are informed by the naturalistic inquiry approach
(Crotty, 1998; Denzin & Lincoln, 2005; Erlandson et al., 1993) and the
phenomenological methodology (Creswell, 2007; Moustakas, 1994; van Manen, 1990).
I obtained the Texas A&M University Institutional Review Board’s (IRB) approval of
the research design before conducting the fieldwork (Appendix A).
Sampling Procedure
The intent of using a phenomenological approach is to explore a phenomenon
extensively and not to generalize to a broader population (Creswell, 2007). To
accomplish this goal, I used purposeful sampling, specifically, a criterion-based
sampling strategy that “leads to selecting information-rich cases for study in depth”
(Patton, 2002, p. 46).
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Selection of the research setting. The setting of this study is an international
public safety training organization that is a state agency in the southwestern United
States. This state agency provides a wide range of technical and skills training programs
aimed at employed workers and those entering the labor force. During fiscal year 2011,
the agency provided training and technical assistance to more than 180,000 people
throughout the world. The agency is a member of one of the largest university systems
in the state and consists of five divisions. Each division uses innovative technology in
training, including the use of tablet technology to replace hardcopy textbooks (Sheehan,
2011) and the creation of a novel simulation support software package (Moats,
Hightower, Ware, & Wall, 2004). The training courses are typically one to five days in
duration, however, some courses do last longer. The courses train public safety
professionals in job-specific skills.
Population and study participants. I focused this study on public safety
professionals who attended training that incorporated the use of innovative technology as
the population for this research study. The public safety community in the United States
has morphed from the tradition of fire services, law enforcement, and emergency
medical services to include more than 10 disciplines. These disciplines include not only
the aforementioned three, but also the disciplines of emergency management, public
works, hospital and health care providers, public health, hazardous materials response,
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state military services, and others. The role of these disciplines is to be the first
responders and first receivers in times of disaster.
While college degrees are preferred for entry into the public safety professions,
they are not required. A college degree does not adequately prepare an individual to
perform the specific tasks of a public safety professionals’ job. Therefore, training is
essential to career development, especially in building skills in emergency response and
management. Within the training itself, it is common that various types of technology
are used to facilitate training courses. In many cases, these technologies are used to
simulate actual working conditions, thus lowering the learning transfer distance.
However, in these cases, the technology used is not a tool that would ever be used on the
job despite it being a primary tool used to conduct the training. This research study is
concerned about this particular nuanced use of technology.
I used a criteria-based sampling strategy to identify and select participants for
this study. In an effort to maintain the ability to provide an in-depth description of the
phenomenon, I limited the study to information-rich participants who met the four
criteria listed below. Each participant:

attended a training course directly related to the performance of his or her
job;

used an innovative technology to facilitate training;

was a member of a public safety discipline (fire service, law enforcement,
emergency management, public works, health care, public health,
hazardous materials response, etc.) at the time of his or her training; and
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
was willing to participate in a 60–90 minute taped interview with the
possibility of a follow-up interview.
I selected participants meeting the criteria from those who had attended training
courses at the organization where I am employed. This purposeful selection strategy
was both practical and feasible, because my organization trained more than 180,000
personnel in fiscal year 2011, with a great majority of those personnel being public
safety professionals. This allows for a diversity of innovative technologies not just a
single type. Additionally, I purposefully selected participants to reflect some diversity in
areas of gender, educational background, and job experience.
Once I identified potential participants, they were contacted through email or in
person to identify their willingness and interest in participating in this study. I drew a
convenience sample from eligible participants based on considerations of time, expense,
and access. I sent each participant a formal introductory letter (Appendix D) and a
demographic data collection tool (Appendix E). The introductory letter (Appendix D)
explained the purpose of the study and the extent of the participant’s involvement. I
used the demographic data tool to acquire background data including research
participants’ experience with various technologies including tablets, smartphones, and
other types of technology. The results from the demographic data tool aided me in
determining the individuals’ experience within their profession and with technology.
I sent participants who were not selected using the criteria an email thanking
them for their interest and informing them that the participants had been selected. These
persons were also informed that unless they explicitly requested otherwise, their names
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and contact information would be held on file for approximately six months in case they
were needed to be a replacement participant in the study or the study was expanded to
include more participants.
I also gave participants an informed consent form (Appendix C) at the time of the
interview. The consent form outlined the nature and purpose of the study, the
participant’s right to stop or withdraw from the study at any time, and his or her right to
review statements made in the interview. The participants were required to sign the
informed consent form in order to participate in the research study.
Data Collection
Aligned with the phenomenological design, in-depth phenomenological
interviewing strategy served as the primary source of data collection. Once I collected
the demographic data, I established a schedule of interviews with the study participants.
I followed an interview protocol (Appendix F) for each interview in order to maintain
consistency throughout the study. Using Asmussen and Creswell (as cited in Creswell,
2002), the interview protocol consisted of the following sections:
1. a header section that includes the date and time of the interview, the
location of the interview, and the identifier for the interviewee;
2. instructions for the interviewer to maintain consistency from one
interview to another;
3. the questions to be asked by the interviewer;
4. areas to write field notes; and
5. a reminder to thank the interviewees.
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I also used probing questions to clarify some responses and to encourage the participants
to elaborate on emerging themes (Creswell, 2002; Patton, 2002). I structured the
interview questions to elicit the lived experience of the participants. Each interview
involved open-ended questions based on the main research question. Specifically, I
sought to ascertain the personal experience of the participants relating to their encounter
with innovative technology used in training applications.
The data collection strategy for this study consisted of in-depth, conversational
interviews of the participants. Interviews were scheduled so that they could be
conducted after the participants’ training had concluded. These interviews attempted to
better understand the lived experience of the participants. Each interview was video
recorded and took between 40 and 75 minutes.
I expected to receive in-depth descriptions of the interviewees’ experiences with
technology inside and outside of the classroom. I observed them during the interviews
and recorded their body language, vocal tone, and pitch, as well as expressions, as they
related their experiences. In addition, I made field notes for the purpose of documenting
the interview and the setting (Patton, 2002). Field notes are essential tools in qualitative
research (Creswell, 2002; Patton, 2002) because they contribute to the richness of the
data. Finally, I video recorded the interviews for later reference, and the recordings were
transcribed either by me or a professional transcription service as soon as possible
following the interviews.
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Data Analysis
Data analysis for qualitative data is a meticulous and time-consuming process.
To analyze the data, I followed a five-step process outlined by Ruona (2005) (1) sensing
themes, (2) constant comparison, (3) recursiveness, (4) inductive and deductive thinking,
and (5) interpretation to generate meaning (p. 236).
Sensing themes. Sensing themes is a process in which patterns are seen from
seemingly random information gathered during data collection. The process requires
that the researcher be immersed in the data and remain open to detect the patterns. In
other words, the researcher must be able to see the “codable moment” (Ruona, 2005, p.
237).
Constant comparison. The constant comparison method was developed by
Glaser and Strauss (1967). This method is a continual comparison of the data
throughout the process. I explain how this process was implemented in Stage Two:
Familiarization.
Recursiveness. Recursivness is a “simultaneous process of data collection and
analysis” (Ruona, 2005, p. 237). To be true to this process, I began my analysis almost
as soon as I started the interviews. Initially, I conducted three pilot interviews, had them
transcribed, and reviewed the transcriptions to identify predominant themes. As a result,
I was able to adjust probes and identify emerging themes. I maintained this recursive
process throughout the data collection and data analysis process.
Inductive and deductive thinking. Inductive thinking is a process of building
and constructing a theory or concept from the data; whereas deductive thinking is a
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process of testing the theory or concept to prove or disprove (Ruona, 2005). These
processes were employed throughout the research processes and are inherently built into
the other components.
Interpretations to generate meaning. Like inductive and deductive thinking,
the process of interpretation to make meaning is naturally embedded in the processes.
This process is much like putting together a jigsaw puzzle upside down and in the dark.
In other cases, it is like pinning together scraps of cloth with straight pins, unpinning,
rearranging, and re-pinning to make a pattern that is somehow pleasing because it is a
reflection of the understood new reality, in other words, a theory. Ruona (2005) explains
this best by writing “We are, in essence, engaging in theory building…[in which] the
theory is derived “inductively from the ‘real world’ to enhance our understanding”
(Turnbull, 2002, p. 319)” (p. 239).
Four stages of data analysis. I accomplished these five-steps through four
stages (Ruona, 2005).
Stage 1: data preparation
Once I collected the data, the video recordings were immediately transcribed and
field notes were typed. The goal of this stage is to organize and format the data so that
the analysis process can begin. During this stage, I read and re-read the transcribed
interviews while watching the video of the interview to ensure accuracy of the
transcripts. During this part of the process, I began to observe some contradictions
between what the participant said and what their body language conveyed. For example,
a participant may have stated that he or she felt comfortable using the innovative
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technology; however his or her body language clearly revealed a level of discomfort as
the memory of the event was recalled. These contradictions between the spoken words
and the physical reaction would have been impossible to identify without the video
recordings.
During this stage, I also assigned each participant a pseudonym to ensure
anonymity and protect the privacy of each participant. After this was completed for each
interview, I created a six column table that allowed me to have a column for (a) coding
of the response, (b) the participant identifier, (c) the question number, (d) the sequence
number for each response, (e) the actual response, and (f) any comments I may need to
make. Through the use of my word processing application, I then formed a table around
the individual responses.
Stage 2: familiarization
The goal of this stage is to engage the data and begin the analysis. During this
stage, I was able to use the tables I created in stage 1 and my research journal to record
what I learned from the review of the transcripts. I also began separating the nuggets
representing themes and initial patterns that emerged as I became more and more
familiar with the data. For the purposes of this research study, themes are expressions or
“structures of experience” (van Manen, 1990, p. 79) and can be in the form of
“‘significant statements’[sic], sentences, or quotes that provide an understanding of how
participants experienced the phenomenon” (Creswell, 2007, p. 61). Moreover, themes
are a form of capturing the phenomenon—the lived experience, not tangible items (van
Manen, 1990).
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Stage 3: coding
Stage 3 is a continuation of stage 2, but with a greater intensity on the analysis.
This is where the segmenting and coding takes place. At this stage, I removed the
interviewer’s comments and examined the transcripts in great detail. Using the constant
comparison technique (Glaser & Strauss, 1967), I began creating themes that fell into the
initial categories created in stage 2. Initially, 10 major categories were created with each
having between two and nine subordinate codes. The list of codes was created based on
the data, not the other way around.
The constant comparative method developed by Glaser and Strauss (1967)
allowed me to organize the data into meaningful categories (themes) by constantly
comparing interviews within interviews and against other interviews (Merriam, 1998;
Ruona, 2005). As the themes initially emerged, they were grouped or horizontalized
(Moustakas, 1994). I conducted this step in two waves of review and reflection. In the
first wave I thoroughly read each interview transcript in context and identified and
assigned codes. The second wave took place a few days later. In this wave I read the
transcripts again and reviewed the assigned codes. During this wave, I created
additional codes as needed. In doing this, I made important decisions about the scope
and focus of the study, as well as developed additional questions to further guide the
research. In some cases, I recoded data to a more appropriate code. I recorded each
code in my research journal.
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Stage 4: merging and working with the data to generate meaning
Stage 4 is the final stage of Ruona’s (2005) process. In this stage, I merged all of
the interviews into a single table. This allowed me to conduct group-level analysis. In
this table, I was able to sort the data in several ways: by code number; by question
number; and by participant. At this point, I evaluated each expression using two criteria:
(a) Does the expression contain an experience that is necessary for the reader to
understand the experience? and (b) Can it be abstracted and labeled (Moustakas, 1994)?
If the expression did not meet these two criteria, I eliminated it; I grouped those
expressions that met the criteria into “clusters of meaning” (Creswell, 2007, p. 61). I
deleted incompatible expressions or those that were not specifically and clearly stated in
the complete transcription. From these, I created interpretations of the experiences,
called textural descriptions, for each participant (Creswell, 2007; Moustakas, 1994). I
also created structural descriptions, or interpretations of the expressions that describe
how the context or setting influenced the participant’s experience of the phenomenon
(Creswell, 2007). I then synthesized these descriptions for each individual to create
textural –structural descriptions. From these, I created a composite description of the
meanings and essences of the experience to represent the group as a whole (Creswell,
2007; Moustakas, 1994).
This recursive process began with the first interview and continued until a
saturation of the categories occurred (Ruona, 2005). Egan (2002) writes that “data
saturation is evident when data collection no longer contributes to elaboration of the
phenomenon being investigated…It is left to the discretion of the researcher to
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determine the adequacy…” (p. 286). To determine when saturation was reached, I
constructed a table to track the categories that were the focus of the study. I created this
table well after the second wave of coding was completed to avoid artificially assigning
data into categories/codes.
Ethical Issues
I took several steps throughout the course of this study to ensure a high ethical
standard. First, I successfully completed the Collaborative Institutional Training
Initiative (CITI) program requirements for the Course in the Protection of Human
Subjects: Social and Behavioral Research for Investigators and Key Study Personnel.
Second, I followed the guidelines provided by the Texas A&M University IRB.
Third, I provided each participant an informed consent form prior to participating
in the study. The form explained their rights, including the right to withdraw at any time
before, during, and after the study. To protect the confidentiality of the participants, I
assigned a code to the video recordings, transcriptions of each interview, and my field
notes. I kept all study-related data on a separate media drive and encrypted it to avoid
unauthorized access to the files. I kept the electronic and hardcopy files in a secured
drawer in my home office; these files will be destroyed seven years after the completion
of the research project. The informed consent form explicitly states that by signing the
form, participants grant me permission to publish the results in a thesis or other
publications with the provision that the quotations will be anonymous.
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Trustworthiness
In quantitative research, reliability and validity are key concepts to explain the
soundness of the research. While these terms are not used in qualitative research, the
term trustworthiness is used to refer to the soundness of the research (Merriam, 1998).
Lincoln and Guba (1985) proposed a framework of four constructs to assess the
soundness of qualitative research: (a) credibility, (b) transferability, (c) dependability,
and (d) confirmability (Marshall & Rossman, 1999; Schwandt, 2001).
Credibility
Credibility refers to the relationship between the “constructed realities” in the
minds of the participants and the realities attributed to them (Erlandson et al., 1993, p.
30). Credibility is the demonstration that the research was conducted in such a way that
it accurately identifies and describes the subject and context. More importantly, Patton
(2002) suggests that the credibility of a qualitative inquiry rests on three criterion: (a) the
rigor of the research methods and techniques; (b) the credibility of the researcher; and
(c) “a fundamental appreciation of naturalistic inquiry, qualitative methods, inductive
analysis, and holistic thinking (p. 461). Lincoln and Guba (1985) provide several
techniques to achieve credibility that were used in this study. In what follows, I have
detailed the techniques I employed during this study.
Prolonged engagement. Prolonged engagement is a technique in which the
researcher is immersed in the context being studied (Erlandson et al., 1993). This
technique helps the researcher ensure that he or she can completely understand the
context. Additionally, this also helps build trust relationships with the participants that
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ultimately reduce the distortion of data created by biases and the researcher’s impact on
the context (Erlandson et al., 1993). To accomplish this, I provided each participant the
opportunity to be interviewed in a classroom, at his or her office, or in at a neutral site.
All but one of the participants chose to be interviewed in a classroom. Another promise
of prolonged engagement is the ability to learn the lay of the land. Although this is a
potential bias, my experience with the programs involved in this study provided ample
opportunity to understand the context and nuances of the programs. By spending a
significant amount of time in the classroom where the specific innovative and/or
emerging technologies were used, I was able to minimize the distortions of my presence.
Referential adequacy. From the outset of this study, I made the conscious
choice to video record each of interviews in this study so that I would be able to go back
and watch the mannerisms of the participants, listen to the audio, and remind myself of
the moments that synchronize with my field notes and reflexive research journal well
after the interviews had concluded. Lincoln and Guba (1985) suggest that these
recordings and the other data serve as “benchmarks against which later data analyses and
interpretations…could be tested for adequacy” (p. 313).
Triangulation. The central point of triangulation is to examine a conclusion
from multiple vantage points (Patton, 2002; Schwandt, 2001). I used a variety of
strategies to triangulate, or corroborate evidence in descriptions and themes, to ensure
the accuracy of this study (Creswell, 2002; Schwandt, 2001). These strategies included:
(a) comparing the multiple accounts of the lived experience of encountering innovative
technologies in training applications, (b) keeping a researcher’s journal to journal my
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experiences and bracket my biases, and (c) using multiple types of data sources (e.g.,
field notes, transcripts, video recordings, etc.).
Peer debriefing. Peer debriefing provides the researcher an opportunity to “step
out of the context being studied to review preconceptions, insights, and analyses with
professionals outside the context who have enough general understanding of the study to
debrief the researcher and provide feedback…” (Erlandson et al., 1993, p. 31). I
accomplished this through two distinct groups. First, I belong to a group of scholarpractitioners that convenes to coach, mentor, and debrief one another as we continue on
our scholarly journey. This group meets Lincoln and Guba’s (1985) description of the
“disinterested peer” (p. 308). Through these debriefings, I was able to discuss my biases
and probe other aspects of the study that I had been mulling. In most cases, this was
helpful to the point of being therapeutic, because I was able to discuss the struggles and
challenges of the process that may have otherwise tainted my judgment with peers
(Lincoln & Guba, 1985). Second, throughout the dissertation process, I have engaged
my doctoral committee for counsel and guidance. Both of these have provided me a
trusted outlet to vent, ponder, and plot this research project.
Member checking. Member checking is when the “data, analytic categories,
interpretations, and conclusions are tested with members of those stakeholding groups
from whom the data were originally collected” (Lincoln & Guba, 1985, p. 314). This
process provided the study participants an opportunity to review the results to ensure that
I correctly interpreted and described their experience (Creswell, 2002; Erlandson et al.,
1993; Merriam, 1998). It also allowed me an opportunity to reflect more deeply on the
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stories and data to ensure that I was treating it and these experiences with the deep
respect they deserve. This strategy resulted in participants agreeing with the
interpretation and description or provided me an opportunity to make changes until the
participants agreed with the interpretation. Participants were given opportunities to
review the descriptions each time changes were made. The cumulative result of these
triangulation strategies has produced a research study that accurately represents the lived
experience of public safety professionals who have encountered innovative technology
in training applications.
Transferability
Transferability addresses whether the research findings will be useful to those
with similar situations with similar research questions (Erlandson et al., 1993). While
positivists refer to external validity, this concept is not possible in a naturalist study. At
best, the reader must make the determination on whether the context and the results of
the study are transferable. The only ability I have to impact transferability is to write a
“thick description” (Lincoln & Guba, 1985, p. 316) that provides the reader with enough
information to make the transferability decision.
Dependability
Dependability relates to the consistency of a study or the ability to replicate the
study (Lincoln & Guba, 1985). However, replicating an interpretivist study is
problematic given the ever-changing social world that is constantly being constructed
(Marshall & Rossman, 1999). Therefore, dependability is addressed as the “researcher
attempts to account for the changing conditions in the phenomenon … and changes in
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the design by an increasingly refined understanding of the setting” (Marshall &
Rossman, 1999, p. 194).
Lincoln and Guba (1985) propose multiple strategies to address dependability.
For this study, I have chosen to use an “inquiry audit” (Lincoln & Guba, 1985, p. 317).
This audit is analogous to a fiscal audit in which an individual is called in to authenticate
financial accounts. In the case of an inquiry audit, the auditors are my doctoral advisory
committee; they examined both the process and the product of my inquiry (Lincoln &
Guba, 1985). Their seal of authentication will be evidenced by the completed signature
sheet that covers this dissertation.
Confirmability
Erlandson et al. (1993) citing Lincoln and Guba (1985) write “an inquiry is
judged in terms of the degree to which its findings are the product of the focus of its
inquiry and not of the biases of the researcher” (p. 34). Confirmability, in the positivist
perspective, is used to address objectivity of the researcher; however, as I have
previously stated, qualitative studies are subjective and therefore not possible to be
replicated given the changing social context. The confirmability construct is still
possible to address because it is intended to ask the question: Can the findings of one
researcher be confirmed by another? (Marshall & Rossman, 1999). Lincoln and Guba
(1985), as well as Erlandson et al. (1993), suggest that it is possible to accomplish
dependability and confirmability through the inquiry audit. To accomplish this, an audit
trail must be patent. Halpren (as cited in Lincoln & Guba, 1985) suggests that the audit
trail consists of several categories of materials: (a) raw data, (b) data reduction and
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analysis products, (c) data reconstruction and synthesis products, (d) process notes, (e)
materials relating to the intentions and dispositions, and (e) instrument development
information. Through the dissertation process, these have been reviewed, revised, and
reviewed again by my doctoral advisory committee.
Role of the Researcher
Denzin and Lincoln (2005) invoke the image of the qualitative researcher as a
maker of quilts, the bricoleur. This metaphor suggests that the researcher must piece
together the squares of knowledge, even if the quilt-maker must “invent, or piece
together, new tools or techniques…” (Denzin & Lincoln, 2005, p. 4). It is with this
metaphoric image in mind that I understood my role as I conducted this research. In the
subsequent paragraphs, I describe my position, including my experiences, assumptions,
education, and career life.
Researcher’s Position
In phenomenological research, it is widely held that the researcher cannot be
separated from his or her own biases and beliefs (Annells, 2006; Groenewald, 2004;
Moustakas, 1994; Ruona, 2005; van Manen, 1990). Likewise, it is widely held that “a
researcher’s epistemology … is literally her theory of knowledge, which serves to decide
how the social phenomena will be studied” (Groenewald, 2004, p. 5). However, one
significant issue that influenced this study is that I was the primary instrument for this
study. There are advantages to this, but also cautions that should be well understood by
the researcher. Among the advantages are that the researcher is able to adapt and adjust
to the research setting to obtain rich and meaningful information. A disadvantage is that
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the researcher is human and, therefore, has biases and assumptions that influence the
study. This means that mistakes will be made and personal biases cannot be completely
avoided. Therefore, researchers conducting qualitative research must be very aware of
these factors and their influence on the findings of the research.
Van Manen (1990) suggests that the researcher’s personal experience is the
starting point for a phenomenological study and nothing could be truer for this study.
This study lies in the nexus of my professional and academic careers to this point.
Because of this, I have certain assumptions that are a source of bias (Agee, 2002;
Merriam, 1998). I have a long career of public service working for local, state, and
federal governments, including service in the United States Navy as a medic.
Consequently, I have experienced a significant amount of the available training to the
public safety disciplines. Moreover, for more than two decades, I have developed
training, facilitated exercises, and designed simulations used to train public safety
personnel around the world. Throughout my youth and adulthood, I have witnessed the
positive impact that training has had on improving the preparedness of public safety
personnel. I have observed how innovative approaches to training have captured the
individuals’ imagination and made a marked improvement in their performance. I have
also been the recipient of poorly designed and executed training that left me angry and
empty.
I am also a self-professed techno-geek and, as such, an advocate for the use of
technology, when appropriate. I have taken opportunities to experiment with and use
many innovative technologies in emergency response operations and in the execution of
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my job, as well as public safety training. Over my career, I have been recognized for the
use innovative technology in public safety training courses. Unfortunately, I have also
seen the effects of when technology is used improperly in training, including increased
transfer of training and decreased participant satisfaction. I am a firm believer that
technology used for the sake of using technology is doomed to reap unsatisfactory
results in training performance. Technology must be carefully integrated into the
training.
I have taken care throughout this process to ensure that my life experiences are
not the primary focus of the study. Prior to conducting the interviews, I created “a
personal description of the lived experience” (van Manen, 1990, p. 54). In writing this
description of my personal experience, absent any interpretations or explanations, I have
been able to identify my own biases and identify potential issues that will recur in the
other interviews. As van Manen (1990) states “…the phenomenologist knows that one’s
own experiences are also the possible experiences of others” (p. 54).
Chapter Summary
This chapter addressed the methodological issues related to this study. The
chapter provided a restatement of the research purpose and question: What is the
experience of public safety professionals who are required to use innovative or emerging
technology in face-to-face training? This chapter also discussed the research paradigm
for the study, including a justification for and description of hermeneutic
phenomenology. The chapter provided descriptions of the research setting, population,
and sampling techniques employed in the study, as well as data collection procedures
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and analysis process. The chapter concluded with a description of the researcher’s role
and the strategies employed to ensure the trustworthiness of the study.
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CHAPTER IV
FINDINGS
The purpose of this hermeneutic phenomenological study was to describe the
lived experience of public safety professionals as they encounter innovative technology
in training applications. This research study was based on a single question: What is the
experience of public safety trainees who are required to use innovative technology in
face to face training? To address this question, six public safety trainees who completed
a training course using innovative technology were interviewed. The interviews were
transcribed verbatim by a professional transcriptionist and me. In addition, observational
data, field notes, and videotaped data were collected. All these data were analyzed to
elicit themes which are reported in this chapter.
This chapter presents major findings related to the research question. The chapter
begins with an introduction of the research context. This is followed by descriptions of
the study participants. Participants were assigned a pseudonym to protect their
confidentiality. The profile of each participant provides the context in which major
themes emerge through the data analysis process. Direct quotes are included to better
understand each participant. Each quote was identified by a code (e.g. Everett, Q1T2),
indicating the location of the direct quote. Data analysis was conducted using Ruona’s
(2005) five step process consisting of: (a) sensing themes, (b) constant comparison, (c)
recursiveness, (d) inductive and deductive thinking, and (e) interpretation to generate
meaning. Marshall and Rossman (1999) point out that this process “entails uncovering
patterns, themes, and categories” (p. 155). These patterns, themes, and categories enable
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me to better understand the meaning of the participants’ world as described by them.
Following the participant profiles is the report of the major themes that emerged from
the data analysis.
The Training Context
Innovative technologies were featured in the training programs selected for this
study. One of innovative technologies used was a computer-supported simulation used to
facilitate multiple scenario-based practical decision-making exercises. The second
technology was an iPad used as both an e-reader and a photo viewer. How these
technologies were used to assist training is described below.
The Computer-based Simulation
A unique, computer-based simulation was used to support the delivery of
practical scenarios. These scenarios provided a context for decision-making through
incident management exercises. Three of the study participants were trainees in a 28hour training course included approximately 45 participants with varying levels of
experience from emergency services organizations across the United States. The
simulation was developed specifically for this course. It also provided participants
situational awareness information about the unfolding incident, including graphic
displays of map data, resource deployment, and video segments that represented
television news. However, the simulation was not intended to be used outside of the
training facility; therefore, it had no operational capabilities.
The course took place in a large training room with more than 50 computers,
three large (10’ X 10’) projected displays, and artifacts that made the room look like an
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incident command post used in the management of large-scale incidents. The course had
18 instructors and role players who were subject matter experts in incident management
and the operation of the simulation.
iPads
iPads were used in several law enforcement oriented courses to support practical
application activities and as an e-reader. Three of the participants in this study attended a
40-hour course that used the iPad as a photo viewer and an e-reader to view the course
participant manual. Participants were not given a printed copy of the participant manual.
Each course had approximately 20 participants. In addition, the participants were
required to use a single lens reflex (SLR) digital camera and electronic flash to take
photos of staged crime scenes. The course was intended to teach crime scene
investigators and detectives proper photographic technique. According to the course
description, “The Forensic Photography I course addresses the basic concepts of
photography and their application to thorough, professional crime scene documentation.
Course instruction is through lecture, case review, and application exercises” (TEEX,
2013).
Participant Profiles
Table 2 provides a summary of the six participants in this study. Five men and
one woman were interviewed in this study. Four of the six interviewees are still active
members of emergency services organizations; two are retired, although one still
volunteers his time as a reserve deputy sheriff. The remaining interviewee retired and
was employed as a part-time instructor for an emergency services training organization
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in the southwest United States. Two of the six interviewees have had a career primarily
in the fire service spanning more than 25 years. The remaining four participants are law
enforcement professionals with experience ranging from less than one year to more than
25 years.
Everett
Everett is one of the most experienced participants in the study. At the time of
the interview, he was a career firefighter in his 50s, working in a large, west coast
metropolitan fire department. He had more than 25 years of experience in the fire service
and at the time of the interview, he was working as a Battalion Chief supervising a large
section of a metropolitan city’s fire response efforts. His duties included supervising
multiple fire companies in the central area of his city including overseeing the fire
response and preparedness efforts for more than one million citizens. Everett had been
an instructor for more than two decades and was an instructor at a large emergency
services training organization. Everett was experienced with technology such as
smartphones and computers. Based on his experience with technology, it was clear that
Everett’s digital personality can best be described as a digital settler.
I interviewed Everett on a day when he had been teaching a course to a group of
about 48 first responders from various U.S. communities. Immediately before our
meeting, I observed him in the classroom with his students. He is a man of medium build
that stands straight. Even after a fast-paced nine hour day, the starched white shirt and
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Table 2
Profiles of Participants
1
Name
Age
Range
Everett
51-60
Juan
61-75
Terrence
Formal Role at
time of
Training
Captain
2
Role
3
Discipline
4
5
Battalion
Chief
Fire
Emergency
services
experience
> 25 years
Emergency
Management
Coordinator
Retired
Fire
> 25 years
Yes
Simulation
41-50
Instructor
Instructor
Law
> 25 years
Yes
Simulation &
PowerPoint
Rusty
31-40
Detective
Detective
Law
11-15 years
Yes
iPad
Bobby
61-75
Reserve
Investigator
Reserve
Investigator
Law
11-15 years
No
iPad
Teresa
23-30
Undergraduate
Student
Crime
Scene
Technician
Law
< 1 year
No
iPad
1
Instructor
experience
Innovative
technology
Yes
Simulation
Participants were assigned pseudonyms to protect their identities during analysis and reporting of the findings.
This indicates the role at the time of the interview. This information was provided by each participant during the interviews.
3
This indicates the emergency services discipline in which the participant spent the majority of their time.
4
This is accurate as of the date the information was provided (i.e., date of the individual interview). The information was informed by the demographic
questionnaire and the interviews.
5
This was based on information gathered during the interviews.
2
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dark blue pants were still crisp and fresh. One of the first things that I noticed about
Everett was his ability to relate to the course participants. He was confident and
definitely in charge of his students. At the same time, he was gentle and encouraging his
students as he coached them through the important decisions they needed to make. His
ability to relate and communicate equipped him to engage his students and they listened
attentively as Everett shared his advice based on the years of experience.
After Everett completed his work for the day, we walked across the hall to a
small, quiet breakout room immediately adjacent to an expansive, technology-laden,
7,500 square foot training room. This room is located in a 37,000 square foot facility
situated in the middle of a 280-acre emergency services training complex. As we sat
down and I set up the camera and audio recorder, Everett’s confidence and enthusiasm
continued to radiate despite the full day of training he had just completed.
Prior to the interview, Everett indicated that he was willing to assist in any way
he could because of his own background as an instructor. He indicated that this research
topic was important to him because it would ultimately equip him to improve the
students’ experiences. This reveals another truth about Everett: as an instructor, he is
most concerned about the trainees he teaches. During the interview, Everett recalled his
experiences encountering the aforementioned computer-supported simulation.
Everett was an articulate and intelligent man. His eyes were bright and alert. As
we started the interview, Everett was relaxed, but engaged and deliberate in his
responses to each question. These things conspired to reveal Everett’s most striking
feature: his command presence. Everett’s deep baritone voice exudes confidence and
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intensity; while his body language and posture demonstrate his ease with the subject at
hand. This left me with a sense that this person is genuine and can be trusted.
As I asked each question, Everett was ready with an answer. It seemed almost as
if he had been given the questions ahead of the interview. The intensity of his answers
revealed his passion for understanding why some people accept, while other reject,
technology used in training. Everett’s answers also revealed his interest in the training
outcomes. He is one of four people interviewed who are also trainers for their home
organization. He admitted that he did not attend the course to learn new content per se as
is the case with most trainees. Instead, Everett stated that his interest in the course was
triggered by his curiosity and perhaps also his skepticism of whether the technology
would provide a suitable training environment for training public safety professionals
who might direct incident response operations:
Ironically, the process that the class taught was a process I was familiar with.
However, I had never participated in an exercise simulation. Most of my
experience was more of hands-on, real-life type experience. I was really
interested in the laboratory-type setting because specifically the skill set
necessary to manage an escalating incident – a crisis if you will – is something
that doesn’t occur frequently...But to be quite honest, I was skeptical whether any
laboratory setting could capture the sense of urgency that’s necessary to build
that skill set to effectively manage a crisis. (Everett, Q1T2-3)
As we continued our discussion, the irony of our setting struck me. As we sat
discussing the massive amounts of innovative technology used to train public safety
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professionals in the training room next door, we were meeting in a room with only a
telephone, fax machine, and a couple blank whiteboards. The walls were bare to the
point that the room echoed as Everett’s deep voice boomed his responses. It was a very
stark contrast to the training room that we had just left.
Juan
Juan is a retired firefighter in his 60s, originally from a medium-sized community
in the southern United States. He has more than 25 years of experience in the fire
service. Juan was also the emergency management coordinator for a rural county in
Texas. In addition to his emergency response experience, Juan has also been an
instructor for public safety and other organizations for much of his career. He has helped
plan and coordinate training courses, as well as develop and deliver practical application
exercises for communities within his home state. At the time of our interview, Juan was
retired, but worked part time for an emergency services training organization.
Juan also chose to reflect on a course with the computer-supported simulation for
his interview. Juan’s encounter with the simulation technology was in an earlier version
of the same course as Everett’s and occurred more than ten years prior to his interview.
Juan explained that prior to taking the training, he had some experience with technology
including computers and console games. This level of experience and exposure probably
places Juan as a digital immigrant before his training experience.
We had arranged the interview a couple days prior to actual the interview. Juan
and I met for our interview after he participated in a week-long training course as role
player. Earlier, on the day of the interview, I observed Juan as he performed his role in
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the exercise control cell. He had just finished a long, nine-hour day that included a sixhour, continuous exercise. During this exercise, Juan portrayed a number of roles
including the mayor and citizens of the city affected by the simulated disaster. He
communicated with the training participants not from a podium, but rather from the
other end of a telephone. As I observed him in action throughout the morning, I noticed
Juan’s proficiency with the simulation. He was very confident in his assigned role and
also in using the technology required to perform the job. Throughout the exercise, Juan
interacted with the simulation he once had a great deal of apprehension about using. The
irony was not lost on either of us.
Juan was clearly tired, but was more than willing to participate in this research
project. He made it clear that this topic was important to him as he felt his experiences
could help others who were coming into future classes. We went to the same room
where Everett and I met the day before. The room was the same: light walls and devoid
of anything seemingly technological, except for a phone and fax machine. However, we
were able to look out the windows and see the large, cavernous training room, full of
computers and three large, blank display screens.
The interview did not last as long as I had anticipated. However, Juan’s
descriptions of his experience were filled with depth and richness that echoed many of
the themes that emerged from Everett’s experiences including: apprehension about using
the technology; the importance of utility to their decision to accept the technology; the
role of the instructors in accepting the technology; the importance of continued exposure
to technology; and the motivations for participating in the training.
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Initially, Juan appeared apprehensive. Juan completed the informed consent form
prior to the interview. Throughout the first half of the interview, I noticed Juan appeared
nervous. So, I tried to relieve some of his anxiety by reassuring him that the interview
was a conversation and there were no right or wrong answers. As he became more
comfortable with the environment and the questions, Juan’s anxiety quickly dissipated.
Juan began to speak more with his hands and provide richer accounts of his experiences.
Like Everett, Juan had a large amount of experience in conducting and
participating in traditional hands-on training and practical exercises. However, he had
little experience in using technology in training. However, Juan disclosed that the
primary motivating factor for him to attend the training was the anticipated requirements
of his future job. At the time he took the training, Juan was about to become a county
emergency management coordinator, charged with establishing his community’s
emergency operations center (EOC).
An EOC is the synergistic result of the combination of a facility, communications
equipment, personnel, and policies that support a community’s response effort to major
disaster incident (Lindell et al., 2007). Proper implementation of an EOC requires a
significant amount of resources and training. In the absence of endless resources,
innovation is an important capability expansion strategy. This looming task was Juan’s
motivation to learn from the innovative use of technology from this course:
I tried to mirror [the training facility] as much as I could. Because, that opened a
lot of minds. It opened my mind up to what I knew I could use in my Emergency
Operations Center. That was very important. I mean, I had worked in the
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Emergency Operations Center when there was just nothing. No technology. That
was it. And, I started using the laptops and I went to the desktops…I built the
EOC for the community that I worked for, and I mirrored it to this [the training
facility], but it was half that size. (Juan, Q1T11-12)
Terrence
Terrence is a retired police officer in his late 40s. He retired after more than 25
years of experience as a police officer including extensive experience as a SWAT team
member and leader, and a bomb disposal technician. After he retired from the police
force, Terrence became a full-time public safety instructor based in the United Arab
Emirates for a U.S.-based emergency services training organization. He had recently left
that position and returned to the United States. At the time of the interview, Terrence had
taken a new position as a full-time instructor for the same simulation-supported training
program as Everett and Juan. He was new to this position, which required him to instruct
a course using the computer-aided simulation.
Terrence stood straight in the classroom and was alert at all times. He was a soft
spoken person with an affable personality, but he seemed to be always ready to jump
into action. As I observed Terrence before and during the interview, he demonstrated a
genuine passion for his job and for teaching public safety professionals. While there
were points during the interview that he clearly missed being a police officer, his
enthusiasm for teaching and for his new position, shined through.
Terrence was the first person to agree to participate in this study. However, he
had to complete the course before he could be interviewed. We met after he completed
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the same course that Everett and Juan had instructed. In the days before his interview, I
observed Terrence as a participant in the course. He interacted with the technology and
the other participants well. He provided a calming and mission-oriented presence
throughout the exercises. He shared his experiences with his fellow participants and did
not appear to be in distress throughout the course, including the practical exercises.
In contrast to Everett and Juan who had both completed the course as participants
several years ago, Terrence was interviewed immediately after training ended. As with
Juan and Everett, Terrence and I also went to the small breakout room adjacent to the
larger training room. Terrence expressed that he is an experienced user of technology,
including computers and SMART phones. He also has a significant amount of
experience playing console games with his children. Like the previous two participants,
Terrence was an instructor with decades of practical experience. However, in contrast to
Everett and Juan, Terrence has also completed multiple online training courses
throughout his career. Based on his descriptions of his previous uses of technology,
Terrence appeared to be a digital settler.
Terrence was motivated to attend the training by the prospect of gaining more
knowledge and to observe and learn the instructor’s role in teaching the simulationsupported course. Terrence also differed from Everett and Juan because he that his
coworkers were watching his performance.
Well, I had a little bit of maybe a different take than the normal student as that I
was gonna be a part of the program, also. So I felt not only I was evaluating
myself in it but I was being evaluated by others at that time. So, that was some of
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the apprehension. But, as far as the technology itself, I initially, again, was
concerned that maybe I wouldn’t pick it up as quickly as I needed to. But I didn’t
feel that was the case after we started getting into it. (Terrence, Q3T18)
Rusty
Rusty is a law enforcement officer in his 30s. At the time of the interview, he
was employed as a criminal investigator by a county sheriff’s department in the
southwestern United States. Rusty had been involved in law enforcement for more than
ten years. Rusty had ample experience with technology, including using computers,
SMART phones and playing console games. He also used multiple tablet-type devices
prior to participating in the training. Like Terrence, Rusty had taken multiple training
courses online throughout his career. In the three years leading up to the interview,
Rusty had completed several courses where iPads were used as a tool in training. Given
his extensive and continued use of technology, Rusty’s digital personality can be
described as a digital native.
Rusty volunteered to be a participant in the study after responding to a request
from the instructor of his latest course. Students in technology assisted training courses
were provided a short description of this research project with contact information. A
training manager distributed the project description to the participants at the beginning
of the course. As a result, Rusty agreed to participate in this study. He was sent an email
with the demographic questionnaire (Appendix E). Once he completed and returned it,
Rusty was recruited as a participant and was confirmed via email (Appendix D). We
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established a time for the interview and arranged to meet at the training facility where I
worked, as it was the most convenient location for Rusty.
Rusty was interviewed once he completed his 40-hour training. As he arrived, I
met him at the door and escorted him to the same room where the other interviews were
conducted. Like Terrence, Rusty is the quintessential police officer. He is tall and fit,
articulate and alert. He would be a welcome sight for someone who is in need and a
menacing presence to a criminal.
As we sat down in the empty breakout room, Rusty was enthusiastic about the
use of technology in training. He was also enthusiastic about the training provided by the
training organization. Rusty chose to share his experiences from a class he took in which
an iPad was used as a primary tool as both an electronic textbook and a photo viewer.
Actually this was not my first [training organization] class…we’ll twist back to
my tech class where they issued an iPad. I took a death investigation a while
back and they used the iPad as the actual book. (Rusty, Q1T1)
Bobby
Bobby has had a distinguished public service career that included long stints in
the U.S. Marine Corps, the U.S. Department of State and as an investigator for a small
city in the southwestern United States. At the time of the interview, Bobby was in his
early 70s. He volunteered his time as a reserve criminal investigator for a county
sheriff’s department in the southwestern United States. He had more than ten years of
experience in law enforcement. Prior to attending the training, he had not yet used a
tablet computer or played console games. However, he had used a smartphone for more
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than four years and a personal computer for more than 30 years. Based on his
background, Bobby is most likely a digital settler.
While we had been friends for many years, Bobby contacted me to volunteer as a
participant in this study after receiving the project description distributed by the training
manager of a course he took. As with Rusty, I sent Bobby an email with the
demographic questionnaire (Appendix E). Once he completed and returned the
questionnaire, it was determined that Bobby met the criteria to participate in this study.
We arranged to meet at the facility where I worked, as it was a convenient location for
Bobby.
Bobby is not an intimidating physical presence like Terrence and Rusty;
however, he is very alert and observant which characterize his role as a criminal
investigator. Throughout our discussion, Bobby sat back in the chair, looking
comfortable and relaxed. Yet, his attention to details, even while we were talking, was
astounding. Bobby is a thoughtful man who has a gift for telling stories. As I listened to
his story, I imagined we were sitting on a park bench in the center of town. His
storytelling ability was entrancing and his stories were filled with rich detail. However,
Bobby’s storytelling ability became a bit of challenge for me as I tried to keep him
focused on stories related to his experiences with innovative technology, rather than any
stories he would like to share.
Bobby recalled his recent experience in a training course where an iPad was used
support the training as a photo viewing device and as an e-reader for participant manual.
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He explained that his motivation for attending the training was to maintain his
professional certifications.
I took it for…three reasons. One, I need 40 hours for my training period. Two, I
am interested in and wanted to learn more about photography. I used to be quite
accomplished at it, but learning how to use the buttons on the digital are the same
but different. And, third, it was free. The attorney general of the great state of
[XXX] is paying for it. (Bobby, Q1T1)
Teresa
At the time of our interview, Teresa was a crime scene technician with a city
police department. She was in her early 20’s and had less than a year of experience in
law enforcement. She was a self-professed gamer, but had only used a smartphone and a
tablet for about three months prior to her first training class. Teresa recalled a course
similar to the ones referenced by Rusty and Bobby, in which an iPad was used to assist
the delivery of the content.
I contacted Teresa after a colleague had seen the description of the study
circulated in a training course and provided me with her name and her contact
information. After a short phone call, Teresa agreed to participate in the study. I sent her
an email with the demographic questionnaire (Appendix E). Once she completed this
and returned it to me, it was determined that she met the criteria to be a participant in
this study. I sent Teresa the interview confirmation email (Appendix D) and we set up a
time for the interview. We arranged to meet at her work facility, as it was the most
convenient location for her.
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I arrived at her headquarters shortly after lunch on the Friday before a major
winter holiday. She led me to a conference room in the police headquarters building. As
we walked through the building, it was clear that many of her colleagues were on leave
or out of the office. The building was deserted and quiet. The walls of the hallways were
adorned with motivational posters and briefing sheets used to provide police officers
with important information. The conference room was warm and displayed the plaques
and trophies that represented the successes of Teresa’s department.
Teresa met me wearing a blue tactical uniform; the typical garb of crime scene
technicians. She was younger and much less experienced than the other participants in
the study; but she looked very confident. She was articulate and intelligent. As we began
the interview, Teresa and I discussed the informed consent form. I asked her permission
to video record the interview. Teresa said it was fine and we started the interview.
Teresa and I discussed her background with technology during the interview. She
explained that she had played video games for much of her life. Teresa’s feeling of being
from “the generation that is into technology” (Teresa, Q1T4) served as a clear indication
of her technological orientation as a digital native. She elaborated on this point later,
solidifying her standing as a digital native:
I have someone in my family who is a technology guru. They basically got the
best of everything, the newest versions of everything, so I get to play around a lot
with stuff like that. I was already pretty much desensitized when I finally got my
hands on one [the technology], got to mess with it. (Teresa, Q5T25)
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Categories and Themes
Five categories emerged from the data analysis: (a) individuals’ perceptions of
technology; (b) individuals’ experience with technology; (c) facilitators of technology
acceptance; (d) barriers to technology acceptance; and (e) other emerging themes of
potential significance. Table 3 presents a summary of major findings from this study.
Each category and the corresponding themes are supported by direct quotes.
Perceptions of Technology
This category relates to how the study participants described their functions of
and attitudes toward technology before, during, and after using it. Four themes emerged
in this category: a) Awestruck; b) Anxiety, frustration, and vulnerability; c) comfortable;
and d) usefulness.
Awestruck. This theme refers to the participants’ feelings of being impressed or
captivated by the technology. The emotion is interpreted as a positive reaction, although
not entirely toward the technology. For example, throughout the interview, Everett
discussed his experiences as a trainee and as a trainer for his department. He continued
to mention his awe of the technology that was used in the course. Not only was he
interested in the “laboratory setting” (Everett, Q1T3) that the training facility and
environment provided. Everett was also enthralled with the innovative applications of
the technology, as well as its usefulness in helping him improve his performance.
More importantly, I was impressed with the technology and the ICP [simulated
incident command post], like most technology in my experience, allows me to
either capture vastly larger amounts of information, process that information and
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Table 3
Summary of Major Findings
Category
#1 – Perceptions of technology
Theme
Awestruck
Anxiety, vulnerability, and frustration
Comfortable
Usefulness
#2 – Experiences with technology
Ease of use
Previous use of /experience with
technology
Created a realistic atmosphere
#3 – Facilitators of technology acceptance
Success with the technology in context
Intervention of the instructors
Meaningful content
Personal drive
#4 – Barriers to technology acceptance
Apprehension from the need to change
from the known practice
Technology as a distraction from learning
Negative experience with technology / bias
against technology
#5 – Other emerging themes
The future use of technology
Advice to training developers
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deliver that information in a much quicker fashion and in a fashion that [is]
recallable and documentable versus the old process of linear-speaking and having
no documentation and only being able to reach a certain amount of people. Using
e-mail in an ICP was something we hadn’t done at that point. And being able to
immediately reach out, even in the e-mail sense, within the ICP was not only a
big plus as far as effective communication; but it has a recallable aspect of it that
we could utilize for post-incident analysis, cost recuperation, a lot of other things
like that. So, I was very impressed with the potential of technology as it relates
to more effective management on a number of different levels. (Everett, Q1T7-8)
Juan also expressed his amazement at the training environment that was
established for the course.
I was so impressed with everything when I walked in. I'm going, "Wow, take a
look at these big screens. What's gonna go on them?" And then, when we started
the process [on] the second day, on the third day, you could see. You had a visual
of everything going on at that incident. [You had] the ability to track your
resources, how they were going, where they were going. (Juan, Q4T25)
Rusty’s enthusiasm was due to the use of technology in the classroom and to the
lengths that the training organization had gone to include the technology and the
equipment needed for implementation in classroom:
I own several iPads. I know they’re not cheap; especially to maintain them and
house them on that scale. The first class that I went to, there was almost 50-some
people there and they [the training organization] were totally prepared for
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everybody to have the equipment needed. Not only did you have the iPad, you
had the accessories that went along with it: the charger, the data cable, and even
in this class they had the adapters for cameras. (Rusty, Q1T10)
Like Rusty, Bobby shared his positive first impressions about the training as he
recognized that the training organization provided the necessary equipment to properly
implement the technology.
I was surprised, pleasantly surprised, that [the training organization] was able to
furnish one to each one of us for this purpose. And I’m sure they have used them
for other purposes except photography. But it made the course seem more high
tech and more interesting from the beginning because it had something new on it.
(Bobby, Q2T11)
After Teresa told me about her experience with the technology in her course, she
recalled her initial reaction to the technology used in her class. Similar to Everett, Juan,
Rusty, and Terrence, Teresa was enamored with the amount of technology in the
classroom. She had a smirk on her face when she explained her amazement.
Well, I thought, “Oh wow, they’ve got a lot of funding if they’re gonna give us
all iPads. And I wonder if I’ll be able to take it home.” That was my main
thought was “There’s no way I’m gonna be able to take this home.” (Teresa,
Q2T13)
Teresa was also impressed with the quality of the technology used in the course
she attended.
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My reaction was this is neat. It’s great. The screen quality is just amazing. We
were able to zoom into our photos and actually blow it up big like if it were on a
regular-sized computer screen. And it had a bunch of different apps. We could
go to the Internet if we needed to look something up. And it’s basically just like
a big iPhone, but I like it because the screen is bigger. You don’t have to
struggle to see something tiny. (Teresa, Q4T17)
Anxiety, vulnerability, and frustration. This theme represented the
participants’ feelings as they encountered technology used in training. Consistently, the
participants experienced feelings of apprehension, being overwhelmed, vulnerability,
and frustration.
According to the participants, various sources contributed to such feelings.
Bobby expressed the challenges he experienced with the physical manipulation of the
technology.
The iPad uses a single, female, connector plug, very tiny pins and there is an up
and a down. But it’s hard to see and it was on an angle. Until the very end, [I]
never still couldn’t plug in the USB adaptor into it or the photo plug adaptor to it
without lots of fidgeting and second and third try and so forth like that. So the
purely mechanical parts of it were still sort of frustrating. (Bobby, Q2T12)
Despite his confidence throughout the interview, Everett surprised me when he
explained that he experienced some anxiety as he was using the technology. Everett
attributed his feelings to his age and little exposure to technology during his “formidable
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educational years” (Everett, Q2T9). He admitted that initially he felt apprehensive,
vulnerable, and clumsy while he was still figuring out how to use the technology.
I can only relate my performance with my fellow students. And the particular
class that I came in there were a lot of young, progressive people in there.
Comparatively speaking, I felt very clumsy initially. One example would be
when we were going through the actual sim and how to negotiate around the
map, draw shapes, and things of that nature. The two people on either side of me
were, from my same department - really my same culture - but younger people
who were more computer literate. They were flying through it and I was
stumbling and clumsy and had to ask for instructor help and subsequent things of
that nature. So I felt very clumsy. (Everett, Q3T16)
Juan also experienced some anxiety, although caused by a different catalyst. He
was overwhelmed by the massive amount of technology in the training facility; and that
he would be expected to use it used to replace what he had customarily done without
technology.
Well, as you know, I attended the very first class, first EIMUC course that was
taught here. And, my very first day here, I said, "Man, what did I get into?"
Because, I was always accustomed to doing lots of hands-on training. (Juan,
Q1T3).
Terrence also admitted that he was initially apprehensive about using the
technology.
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Initially….I had a little background. But, as a student coming in…you’re
apprehensive about: “What all am I gonna need to know? How interactive am I
going to be on a personal level with this? And how quickly can I assimilate the
technology and make it useable through the class not knowing if I’m behind with
other students who may be more familiar or whatever?…As the first scenarios
were being started…you get that apprehension about am I doing this right? Am I
going to the right pages? (Terrence, Q1T6)
However, his apprehension was triggered by being a new instructor in the
program and feeling that many eyes were on him evaluating his performance. Terrence
explained that while he could probably function as a student in the class, the added
pressure of being an instructor in the program led to his feeling of being overwhelmed.
As the interview continued, Terrence disclosed that the sheer amount of information was
overwhelming for him as a student in the training.
The first week when I came in [to work] and it [the simulation] was being shown,
[I was] just kind of getting a taste of it. I was thinking, “Oh wow, this is a lot to
assimilate.” So when I went in as a student, after that first initial involvement and
we’re doing the afternoon scenario, I was a little bit pensive. When I got to the
thing [simulation] and I said, “Oh man, this is a lot to learn.” And not only
thinking about it at that time as a student, but also [as an] instructor … ‘cause I’m
thinking, “I got to know everything about this inside and out, not just as
superficially as a student.” So I kind of had a feeling that I can function as a
student. I felt fine doing that, but then now I need to learn this, and that first day
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or two after. This is a lot to assimilate in a short amount of time as…So I had
both those things going on working. You know, thinking not only as the student
side of it, but the instructor side of it. (Terrence, Q4T21)
Rusty’s experience with the technology was markedly different from that of other
participants in this study. His apprehension, what he characterized as a “cumbersome
feeling”, did not come from the exposure to the technology; instead it came from being
forced to leave some familiar technology behind.
The feeling that I had, it was actually a cumbersome feeling, because everywhere
I go, I already have two tablets. I have the ASUS Transformer pad, and I have an
iPad. So now that I went to a class that required me to sign-out and be
responsible for an iPad. It was a little bit cumbersome, because now I had to
leave – you know, the first day I had to leave my devices at home to use that
device. (Rusty, Q4T15)
In contrast to the other participants in this study, Bobby revealed that he quickly
accepted the innovative technology used in his training, “The iPad was the new gizmo.
It, after a few minutes, was just the same as having a notebook or something else”
(Bobby, Q2T24). However, Bobby struggled with learning to use the technology that
was at the core of the training: a digital camera. For Bobby, this technology presented
some challenges.
The whole course itself was devoted to the technology of digital photography.
And so, I guess, one of the confusing things was, everyone had to have a digital
camera and most had either Canon or a Nikon. Canon and Nikon do everything
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the same as the other one does it; except they have reached some agreement to
label everything completely opposite. So every function is given a different
nomenclature or, it’s called something different. So the technology of the camera
itself was, if anything, the confusing part of the learning...So I would say the
confusing part of the course regarding technology was the subject matter itself,
which was made a little more confusing by everybody using a different
instrument at the same time. (Bobby, Q3T25)
Teresa also experienced frustration with the technology used in the training. In
her case, the technology did not meet her tactile needs.
It wasn’t the same as having a hard copy in your hand. I like to have the feel of a
book in my hand. I can flip to whatever page I need. I can make notes. You
can’t really do that with an iPad. If you do, you have to open up a little make-anote-about-this thing and it’ll mark it, but it’s not the same as being able to just
look down and see what you’ve written. So, it was a little frustrating. (Teresa,
Q2T10a)
Comfort. This includes participants’ feelings of comfort with and willingness to
use the technology. This was interpreted as a sign of, at least, partial acceptance of the
technology.
Terrence stated that as his experience with the technology increased, his
understanding of the technology’s utility enhanced as well. This, coupled with minor
coaching from the instructors, eased his apprehension. As his apprehension eased, he
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became more comfortable with the technology. As Terrence noted, his comfort with the
technology heavily influenced his experience with the technology.
It was a very user-friendly system. I felt that with just a little bit of guidance,
you can work your way around the whole system. I enjoyed it. I actually went
from apprehensive on the initial onslaught [laughter] and then felt very
comfortable, even less than midway through the training cycle. By the end, you
felt like you learned the processes. The simulation, the computer system that was
used, truly enhanced the learning experience. I felt very comfortable by the end
of it. (Terrence, Q1T10)
Terrence’s comfort was also bolstered knowing that the technology was designed
by professionals with expertise in his field.
I liked the thought of it [the simulation] being a system that was developed by
professionals and experts in the field. So I expected – I had high expectations for
it. Again, I felt comfortable with it fairly quickly into the training. (Terrence,
Q2T13)
Everett also became comfortable with the technology as he used it more. As his
comfort level with the technology increased, so did his appreciation for the technology’s
value. As his comfort increased, his initial skepticism also subsided:
After seeing the success and how much more effective it [the simulation] made
me. It quickly erased all that apprehension and initial confusion I may have had,
and hence made me more receptive to now different types of newer technologies
that come. (Everett, Q2T14)
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Usefulness. This theme is used to discuss the participant’s appreciation for how
the technology helped them enhance their performance (e.g. in training and/or on the
job). This is a critical theme as nearly all of the participants emphasized the usefulness
of technology multiple times throughout their interviews.
Everett stated that his apprehension and vulnerability disappeared as he saw the
utility of the technology in helping him do his job better (Everett, Q1T7). Utility was a
recurring theme for him. At several points throughout the interview, he was quick to
point out that his exposure to the technologies in his training allowed him to be more
receptive to other innovative technologies.
Once I got comfortable with it, I began to see the value in the daily discharge of
routines. That is probably the biggest value that I see now in technology. Both in
training and real-life incidents, I’m able to utilize that [technology] and be much
more effective on a multitude of levels; not only effective management of
incidents, but utilizing lessons learned for subsequent training, being able to
document that stuff in a digital sense or whatever. It’s just made me a lot more
effective and a lot more professional. (Everett, Q1T12)
Juan stated as his exposure to the technology increased, he was also able to
understand the utility of the technology and his comfort with the technology also
increased.
The first day was very interesting trying to learn [the] EM*ES program. After the
end of the first day, I said, "Whoa!” I'm wondering if I'm going to be able to
handle all this." Well, the second day, it worked out a lot easier. I said, "Oh, this
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makes everything run smoother. You can track it [resources] better. There is no
large paper shuffle that you have to worry about. The technology itself was
outstanding. (Juan, Q1T5-6)
Juan shared that as he continued to use the technology he developed a better
understanding of the technology’s applicability to his current job. The utility of the
technology made him more efficient as a large-scale incident manager. This ultimately
made it possible for him to improve his job performance, even though he would not see
the simulation outside of the classroom.
Well, again, that very first day was kind of way over my head. The second day, I
was able to understand a whole lot more and have the opportunity to use it more.
Now, I'll say it simplified the process required to manage the incident itself. We
had everything in the computer system: all your resources, you had the process to
follow, the [U.S. Coast Guard Operational] planning “P” was readily available all
the time just so you could follow that process. (Juan, Q1T9-10)
Later, Juan elaborated on the utility he saw in the technology and why it was
important for him to accept the technology.
I liked it because I had the opportunity to learn something different. Something
that I knew was gonna keep moving forward. The old dog and pony show were
gone. Now we were driving automobiles and we didn't have to feed them that
much. But, the system itself just opened a lot more doors. The availability of
[information] if you don't know this answer, shoot to the Internet. You're right
back into it. You're done. You've got your answer. You could always find
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resources that you may not know of or you just may have a question on. For
example, how much fuel is in a tank? Above ground tank? An oil pit? A
refinery? Look it up. One point five billion barrels. I know, because I looked it
up. So, it's things like that that just simplifies; it expedites everything. The
process where you're not sitting there spinning your wheels. (Juan, Q2T14)
While Rusty had several tablet devices, he had not encountered an electronic book
before. However, his perspective was positive.
I would say I had experience using an iPad. Therefore, it was not a difficult
drama for me. I was new to e-books. I did not exactly know how e-books
worked. But, once we got in there and the instructor went through the initial, I
realized that all it was is just a PDF file and you’re just scrolling through it page
by page. Once I realized that’s what it was I had, a good feel and a handle about
what I was experiencing. (Rusty, Q2T12)
Bobby surprised me a bit in our conversation as he explained the importance of
the technology’s utility in his decision to accept technology: “Yeah. I approve
technology. I approve anything that can improve work and make whatever you’re doing
simpler or better is good” (Bobby, Q5T43). Bobby’s practical view continued, “And if it
can also be done while costing less, than the previous method, that’s even better”
(Bobby, Q5T44). These statements also reaffirm what the other study participants have
noted to this point: the utility of the technology used in training is paramount to
acceptance by the user.
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Experiences with Technology
This category consists of the participants’ reported experiences with technology.
Three themes emerged in this category. These themes are: a) ease of use; b) previous use
of or experience with technology; and c) technology created a realistic atmosphere.
Ease of use. This theme addresses the participants’ feelings concerning the
operability of the technology. Words used by the participants to describe their
experience with technology included “intuitive,” “convenient,” “user friendly,” and
“easy to use.”
Rusty explained that his previous experience with the iPad made the technology
easier to use in training, despite that he had not used the technology in the way it was
being used in the training.
My first impression was like, “Wow,” because that’s not an easy feat to issue 30
to 50 iPads for a class, but I’m very familiar with an iPad. I thought it was very,
very beneficial for me as a person; it was user-friendly on my scope. (Rusty,
Q1T3-4)
Teresa discussed the iPad’s ease of use and how she felt about it:
It was just the ease of having pretty much everything I would need right there at
my fingertips and it was lightweight. It’s not like a laptop. I have a laptop. But I
have to have a big enough screen; and if you have a big screen, it’s heavy. I don’t
carry it with me because of that; but [with] an iPad, they’ve compacted
everything into this book-sized object. So it’s just really convenient in my
opinion. (Teresa, Q4T18)
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Bobby continued with the theme citing the ease of use of the Apple products
being the reason that people like them so well:
I suspect that there are a few, just as there are a few physical klutzes, who just are
not good mechanical things. There’s bound to be a few people, who just don’t
learn technology or new technological devices automatically, intuitively. And
this particular colleague of mine is definitely one of them. And so I would
suspect that, in any given group, there’s gonna be at least one or two people that
introducing a new technology into their environment or as a teaching tool or
something like that may either be difficult or time consuming or, in the future,
even impossible. I don’t know. Apple makes things intuitive and it makes things
simple; which is why people like it. (Bobby, Q5T55)
Previous use of technology or experience prior to the training. This
represents the participant’s previous use of, or experience with, technology prior to
taking the training that discussed in the interview.
During this interview, Terrence recalled two experiences of encountering
innovative technology. His first experience from early in his career was the use of
PowerPoint to replace 35 mm slides and transparencies. His second experience was the
use of a computer-supported simulation used to deliver scenario-based training. Terrence
explains his perspective.
Through my experience, almost 30 years of being involved in training or
teaching, I’ve gone through from just PowerPoint coming into play all the way
back to then. Even then, when we went from slides and just handouts to
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PowerPoint’s and the function of that, I thought that was an excellent and great
way to start evolving. I personally always liked the evolution of technology in
the training field. Now and of course that’s got to be driven by the course, itself.
What subject matter is being pushed? Specifically thinking about the
technological changes recently here at [my training organization] as development
of their own software and the pushing of that I think it’s excellent…So, to me it
has great benefit when used appropriately. Sometimes, there’s a learning curve of
getting to that point of: When is it too much? Of course, it’s a changing
generation that’s now growing up with constant video feed, you know, in some
ways. (Terrence, Q1T1a-b, d)
Terrence continued to frame his experience with a note of caution to course
developers about the overuse of technology, even when the technology is a positive
addition to the training.
The way I saw it, we went through kind of a learning process and I think that’s
common with the technology. Like PowerPoint, we went to where it became too
much of a crutch and was used too much. We took away from some of the
interpersonal. It was almost detrimental at times when we used too much of it.
We’d get away from personal interaction or hands-on training…Sometimes, I
like it; but I think it needs to be tempered with some different styles. (Terrence,
Q1T1c-d)
Well into the conversation, Rusty explained that he specializes in cybercrimes
which requires him to use technology extensively. Rusty also noted that his prior
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significant exposure to technology and understanding of the technology’s use had a
significant influence on his willingness to accept technology.
Well, actually to be fair, I probably have a bias because I’m a cyber-investigator;
I do [investigate] high-tech crimes. I’m actually an investigator assigned to a
high-tech crimes unit. Therefore technology is my basic tool of investigation
from day to day. Well, I don’t want to necessarily say is it’s unfair that I have the
bias, but I use technology and I find it effective. (Rusty, Q5T17)
Teresa’s experience with the innovative technology was pleasant. She indicated
that the technology was easy to use and “it wasn’t difficult to adapt to at all” (Teresa,
Q1T3). She stated, “Because I had had experience with an iPhone before, it made it a lot
easier. I guess you could say I’m the generation that is into technology like that”
(Teresa, Q1T4).
The technology created a realistic atmosphere. This theme identified
participants’ perception of the realism created by the technology after experience using
the technology.
Everett and Terrence stressed the importance of creating a realistic atmosphere in
some training situations. This is not surprising given their work experience and the fact
that the course they attended was designed to simulate actual job conditions.
I actually almost like to separate the technology down into a couple different
categories. One was the technology of the simulation which created a realistic
battlefield tempo; you felt like the incident was actually occurring. (Everett,
Q1T4&6)
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Terrence also mentioned the immersive, realistic feel of the training
environment, which was due to the technology, at least in part.
Well, I’ve been on both sides of it. I’ve instructed with it; but also attended the
class recently myself. And so how that was pushed as a student’s viewpoint, I
thought was extremely helpful…Now, I can see it and work it as in every area. I
can see what all the other students are doing. I can see the consistency that
comes from that kind of a system that allowed me as a student to feel immersed
in the training. I can feel almost as close as I can get not actually being there.
(Terrence, Q1T4)
Facilitators of Technology Acceptance
This category consists of experiences that participants indicate positively
impacted their decisions to accept the technology. There are three themes that were
identified in this category: a) success with the technology; b) intervention of the
instructors; and c) the participants’ personal drive.
Success with the technology in context. This theme addresses the participants’
experiences with successes in using the technology and how it impacted the decision to
accept technology.
Earlier in this chapter, Everett explained the importance of seeing success using
the technology.
Now, I’m seeing the past history of these successes; now when something new
comes up, rather than having that initial apprehension, I recall that initial
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apprehension. Now, I am much more receptive and more apt to try, with a
completely open mind, new types of technology. (Everett, Q2T15)
This success had a lasting impact on Everett’s personal appreciation for
technology:
It’s [the technology] made me much more open to it because of the success.
Initially, the impetus was this training session. The subsequent success in the
training session and that three days of training, became the catalyst for me being
much more open-minded. Really, that was kind of just the beginning of my
department’s acceptance of numerous technology tools that we utilize now on a
daily basis. (Everett, Q5T23a)
Everett’s experiences have also success carried over to his department.
It’s always initially a confusing thing because we’re deviating from a past
practice. But every single time, we look back after we’ve used the technology for
three or four years. We look back at the old way we used to do it and we literally
will laugh out loud of how archaic it was compared to how efficient we are now
with the new technology. (Everett, Q5T25)
Juan had a similar reaction after seeing the successes he had in the training.
Well, the second day it worked out a lot easier. I said, "Oh, this makes everything
run smoother. You can track it better. There is no large paper shuffle that you
have to worry about and just the technology itself was outstanding, because I've
used some of this technology when I'd built my EOC, when I became Emergency
Management Coordinator. (Juan, Q1T6)
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Role of the instructors. This theme addresses the impact of the interaction with
the instructors on the participants’ experience.
Everett addressed how the instructors contributed to his experience with the
technology:
The receptiveness of the instructors to be patient and work with me alleviated my
reluctance to ask for more help. And then, the subsequent explanations that I
needed in demonstrations ultimately helped me learn it better. (Everett, Q3T18)
As we discussed the Juan’s experiences with the technology, his experience
explained how important the instructor interventions were. He explained how the
instructors’ assistance eased his apprehension.
The information you guys [the instructors] provided us simplified the knowledge
for me to absorb more knowledge out of that. After the first day, I really felt
good about how to use it [the simulation]. I kept falling off the table every now
and then, but I'd get right back on the table and the instructor was ready [and]
available to provide assistance. (Juan, Q4T23-24)
Terrence also discussed the instructors’ impact on his experience with the
technology: “I quickly found that it was easily acquired and that with just a little bit of
guidance from instructors, by the second scenario you can almost work on your own in
those areas” (Terrence, Q1T10).
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Personal drive. This theme addresses the impact of the participants’ internal
motivations that pushed them to work through the frustration, anxiety and confusion
created during the encounter with the technology.
Early in our discussion, Juan had discussed his motivation for attending the
training. He quickly recognized that he had to change because the technology was
quickly entering the workplace. This served as motivation for him to accept the
technology:
The first day was very interesting, because I had to open up and learn the new
process, the new tech, the new tech stuff that was coming up. So, you know, I
said, "Okay, open mind. We can do this.” (Juan, Q1T4)
Terrence shared a similar experience to Juan’s. Terrence did not feel like
quitting, but he was challenged by the technology. Nevertheless, he was determined that
the technology would not beat him:
Let me think about that for a moment…I can’t think of a specific answer and
about myself where I just said no. I don’t have that personality…I would say,
“No, I can’t do it.” I have – trying to think of a specific incident because I’m sure
I have said, “Wow, this is just too much. I need your help some more.”
(Terrence, Q6bT48)
Barriers to Technology Acceptance
This category consists of experiences that participants indicate potentially
inhibited or negatively impacted their experience with the technology. There are three
themes identified in this category: a) apprehension from the need to change from the
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know practice / resistance to change; b) technology as a distraction from learning; and c)
negative experience with technology or a bias against technology.
Apprehension caused by a change away from current or known practices.
This theme addresses participants’ experiences of anxiety created by the training content
requiring change outside of known practices. Everett was very quick to point out that his
apprehension was not only due to the technology, but also due to the content of the
course pushing him outside of his comfort zone.
Initially, I felt very vulnerable in trusting the machine or even deviating from my
tried and true process that I’ve established over years and years responding to
thousands of incidents. And now suddenly to deviate from that process and
utilize the technology, utilize the machine, resulted in that initial apprehension.
(Everett, Q2T13)
Like Everett, Juan attributed some of his apprehension to the course content
forcing him to rely on a new process that incorporated technology. “You know, what
threw me for a loop was, right off the bat, was it's a new system. I've got to learn this.”
(Juan, Q5T26)
Like Everett, Terrence attributed some of his apprehension to the way that the
course stretched him beyond his comfort zone.
You know I wasn’t scared of it. I didn’t feel like I would be overwhelmed by it.
It just kind of to me felt like a new learning environment and a little apprehensive
about how does this all play out. (Terrence, Q2T17)
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Terrence also suggested that the unique classroom environment, facilitated in
part by the use of the technology, contributed to the apprehension he was feeling as well.
I think the apprehension probably covers most of what I was feeling. You know
some of that is not specifically or completely about the technology. It’s just
being in a new environment. (Terrence, Q2T15)
Technology as a distraction from learning. This theme encompasses
participants’ experiences of technology that detracted from the training and its impact on
the decision to accept technology.
Everett discussed how glitches with the technology affected his experiences with
the technology:
We’ve had glitches. After my exposure and employment here, I became an
exercise designer back home. I did it for the entire [city] region for about a fiveyear period. There were technology glitches. Mostly were operator-error type
things, not so much concept of technology and how that’s applied…My only
concern was that sometimes, amongst skeptical students, if we had a computer
glitch it kind of left a black eye. Much like my success on a positive note, it
could be counterproductive in a negative note if we had some type of glitch that
made a less-than-positive training experience from a technology point of view.
(Everett, Q5aT27)
Rusty echoed Everett’s sentiments. He also felt that the technology can serve as a
distraction from the instruction. For example, an iPad that allows the participant to
indiscriminately surf the web can be a distraction from the instruction of the course.
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It’s more of an entertaining value in that boring part where somebody – and
again it does have a negative adverse because now somebody just wants to play
with a new gadget and not actually learn. It’s kind of a double-edged sword.
(Rusty, Q6T23a)
Everett also discussed the experience he had as a course participant, watching
how his fellow participants allowed the technology to distract them.
It [the technology] forced me to be a little more analytical and really pay
attention, versus some of the other people that were just flying through it. I think
[they] missed some of the instruction because they were steps ahead of the
instruction. (Everett, Q3T18)
Negative experience with technology / bias against technology. This describes
participants’ negative experience with technology, including occasions where the
technology failed to meet the needs of the participants, and how these experiences
influenced their feelings about the technology.
Teresa surprised me as she intimated that the technology did not have the utility
she needed and therefore was not an improvement or enhancement to her training. This
led to her frustration concerning the technology.
It wasn’t the same as having a hard copy in your hand. I like to have the feel of a
book in my hand. I can flip to whatever page I need. I can make notes. You
can’t really do that with an iPad. If you do, you have to open up a little make-anote-about-this thing and it’ll mark it. But it’s not the same as being able to just
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look down and see what you’ve written. So, it was a little frustrating. (Teresa,
Q2T10a)
As we continued with the interview, Teresa was the only participant to reject the
technology used in the training.
In the courses I took after that [first training course], I just didn’t use it. I
stopped using it pretty much except for pictures. The overhead projector
provided all the information I need. They make it to where we really don’t have
to go back and look stuff up unless we want to. It was meant as a convenience
I’m sure. But without learning how to use it or just having a little, maybe, an
hour of, “Hey, this is how you use it. This is how you make notes in it.” It was
kind of pointless. (Teresa, Q2T10b)
Bobby had a co-worker who was not as technologically savvy as he was. In fact,
Bobby had become the impromptu technology tutor for his colleague. He helped his
fellow law enforcement officer find his user name and password for an old email
account; register for and start an online training course; and print documents needed to
complete the course. As he recounted this experience, Bobby said, “The point of this is
that some old dogs have a great, great, great deal of trouble learning new tricks. And I
suspect it doesn’t necessarily depend upon age even.” (Bobby, Q5T48)
Other Themes of Importance
This category includes three themes that emerged from the data which is not
directly related to my research questions. They are: a) meaningful content; b) the future
use of technology; and c) the participants’ advice to the developers of future training.
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These three themes are included in this report because they provide useful insights and
values implications for future research and practice.
Meaningful content. This theme addresses the participants’ experience with the
training content, beyond the technology and how the organization and presentation
impacted the participants’ decision to accept technology.
Terrence understood that the training content was oriented toward success and
felt that because of the utility it offered, people are more likely to accept the technology
to better learn the content:
So I think that’s a good point that, even though you can’t walk away with our
software, everything that we do you can use in a hard copy. So, I think that’s a
lot of why they really like it better. They can validate it outside of the classroom.
The processes…the things they’ve learned. They can take those processes and
put them into action…The knowledge, the process knowledge, is valid outside
the room. The electronic forms that we put into the simulation are valid outside
of the classroom and useable. And also…you’ll see a lot of that in the students’
feedback that the simulations were good and that they could actually say this is
something we may encounter. And that, again, makes it something they can use
outside of the classroom. If they thought that this was a simulation, it really is
not valid or it only happened here, then you’re losing a lot of the instructional
and learning value of it. But if they think that can happen all right and it has
happened now that it’s a takeaway for ‘em. (Terrence, Q6dT62)
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Future use of technology. This theme encompasses the participants’ suggestions
for the future use of technology used in training.
The training, specifically the success with the innovative technology, had a
significant effect on Everett and his willingness to accept innovative technologies. He
not only accepted the innovative technologies used in the training course he took; he has
become an advocate for using technologies in his job. He now works to encourage others
to accept innovative technology.
I was totally opened and even now I still see huge reluctance amongst the [my
department’s] membership when that initial confusing phase of a new technology
tool is introduced. What I can do is I usually point back to the confusion…So, the
impetus I think was my success here with the new technology which created a
much more just open-mind environment towards being introduced to new
technologies. (Everett, Q5T23b-25)
Juan shared his vision of how innovative technology would be used in the future
workplace.
The technology that I saw here [in the course] really pushed me to learning more
about the technology, about the electronic, computer systems. Because, you can
forget paperwork. I mean, it's gonna be on tablets...And you're not gonna be
killing anymore trees. So, I really reached out to getting more knowledge of new
technology coming out, and new programs, of course. (Juan, Q5T30)
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Advice to developers. This theme encompasses pieces of advice from the
participants to developers and managers of future training courses who would potentially
incorporate technology into the training.
Near the end of the interview with Juan, provided sage advice to training
developers and training managers concerning the use of technology in training.
User friendly. It's got to be user friendly. Because, if it's not user friendly, you're
gonna get some individuals who do not have a lot of knowledge on computer
usage or programs on the computer that would benefit them. They're gonna fight
you on it. In some cases, some of those individuals just jump right in and go,
“Hey, trial and error, trial and error. That's all I can do. I can't fail on this system.
I can't mess it up.” My big thing is user friendly. It's got to be user friendly.
(Juan, Q6T32)
Terrence offered his recommendations to developers about how to best
implement technology into training. He suggested that the technology should be focused
in training and not added simply to show off the technology. According to Terrence, the
latter situation often becomes a distraction to learning.
I’ll fall back to some of the things that I think of as far as what makes training
exceptional training. The use of the technology is not overwhelming to the
delivery. I would like to think the technology being used, whether it’s the iPads
or whatever, that the students don’t become just immersed in the use of a newfangled piece of equipment and they’re losing some of what’s being delivered to
them in the course, itself. You see that sometimes when you bring a new toy or
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tool into an environment, people will just concentrate on that. Well yeah, that’s a
neat system, a neat computer or whatever, and they sometimes walk away and it
feels like that they didn’t really grasp some of the things we were trying to get
across to ‘em as far as what they need for their abilities and their jobs. So, to
clarify that just a little better, I think the technology and the way it’s going
almost [in] every instance has its positives and negatives. And we as instructors
and trainers have got to see where those are. “Where’s the positives?” “Where’s
the negatives?” “When is the utilization of the PowerPoint’s or the ipads or the
videos, anything we’re able to inject has that now become too much of a wow
factor as opposed to solid instruction?” And sometimes I’ll see instruction and
I’ll think that they’re just glitz and glamour and they’re trying to impress in the
technological advances of their technological abilities, but the depth of
instruction lacks and they try to make up for it in these other realms. So, that’s
my take on it, that it’s excellent until it’s overused and you’re not delivering
material. You’re delivering show. Does that make sense? (Terrence, Q6T28)
Terrence continues this thought by reinforcing that instructional designers,
instructors, and training managers should understand that trainees are all over a spectrum
of technological proficiency. Therefore, he suggests the following.
In our technological advances I think we sometimes leave students behind
because we don’t make it basic enough. I would say that to some developers
please don’t develop it as though it’s you or even your half-life coming in to take
this course. Give us something that the basic student coming in who has very
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little or has a built-in bias ‘cause it’s new to them and gets ‘em outside of their
comfort zone. Let’s make it so that they can come in and that’ll usually once they
get over that mental block that they can’t do it, will pretty quickly catch up to
where you need to be. But if it’s just immediately overwhelming and you leave
‘em there, you’ve lost ‘em for the whole training. (Terrence, Q6aT46-47)
Rusty explained how important it is to ensure that the technology does not
interfere with learning that is to take place during the training.
It’s very effective because learning itself has advantages and disadvantages.
You’re trying to convey something to a person trying to learn, so they have no
concept what you’re trying to teach them. Until they get that depth of
understanding [and] the light bulb goes off. It’s like “Oh, now I get it.” By using
technology you’re able to incorporate more vivid tools. I’ve heard time and time
again somebody’s like, “You know, I can read it but I don’t understand it until I
see it.” Or, people who have learning disabilities with reading, dyslexia; that stuff
comes back out. When they have a visual tool the only visual impairment that,
you know, somebody would have would be eyesight, and that’s kind of a little bit
more limited on a learning ability. So the visual aspect of it is greatly enhancable;
I would say that would be the one thing I’d recommend is keep that focus in
mind because that’s very detrimental in education. (Rusty, Q6T23)
Like the other participants, Bobby offered some advice to developers and
managers of training regarding how to design courses using innovative technology to
increase the potential for technology acceptance. His message to the developers was
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clear: “Don’t make it so complicated that it distracts from the course material, or make
its [the technology’s] use in any way distracting from actually the course material”
(Bobby, Q6T66). He also reiterated a common theme that resonated with many other
study participants: keeping the technology easy to use.
KISS, keep it simple stupid. Whatever technology is being used [should] not
require extensive training to use it by the student. It may require a lot of new
training to use it by the instructor, but they are paid to do that and have time to do
it before the course starts. I suppose don’t assume that everyone immediately
already is at your level of technology to begin with. Survey or have some way of
finding out if everyone is familiar with the basic concepts of the technology that
you’re going to be using. (Bobby, Q6T61)
Teresa offered her advice to the training developers and managers as well. She
stressed the importance of having a choice in using technology is to trainees.
I don’t want to say that they should have to print us off a hard copy of it. I like
the ease of having the books in a thumb drive, so I don’t have to carry around a
big old hard copy. But I feel like we should be given a choice…Because I feel
like some people feel like they may be forced into this new age of
technology…Technology, to me, is very productive. It’s more helpful than it is a
hindrance. But if you just have a certain mindset, you’re not going to be willing
to accept it. Which is why I think if they don’t give us a choice; if they would
teach us at the beginning of class how to use it to our advantage; it might be
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easier for people who are more traditional to get acclimated to it. (Teresa,
Q6T31-34)
Chapter Summary
This chapter presented the lived experiences of six public safety professionals
with varying levels of experience with technology. Each of these professionals attended
a training course that used innovative technology to support the training delivery. The
trainees’ experience reflected that trainees experience a variety of emotions, including
anxiety as they encounter innovative technology used to support training. Their
experiences also indicated that instructors have an important role in affecting the
perceptions of technology used in training. However, after the trainees had an
opportunity to use the technology, they understood the utility of the technology used as it
relates to helping the trainees achieve their goals. Their experiences indicated that they
became more comfortable with the technology as they had the opportunity to use it.
Participants in the study also offered advice to training developers and training manager
concerning how best to incorporate technology in future training courses.
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CHAPTER V
DISCUSSION, RECOMMENDATIONS, AND CONCLUSIONS
The purpose of this study was to understand the experience of public safety
professionals using innovative technology in a training context. I interviewed six public
safety professionals who used innovative technology in a public safety training context
for this study. I used a hermeneutical phenomenological approach to explore the lived
experiences of the participants (van Manen, 1990). This study was guided by a single
research question: What is the experience of public safety trainees who are required to
use innovative or emerging technology in face-to-face training?
The first section of this chapter discusses six conclusions based on an analysis of
major findings derived from lived experiences of six public safety professionals revealed
in Chapter IV. Next, this chapter presents a new conceptual framework that explains the
actions and reactions that participants take as they use innovative technology in a
training context. The chapter concludes with recommendations and implications for
research and practice.
Discussion
I drew six conclusions from a detailed analysis of the major findings revealed in
Chapter IV as follows:
1. An individual’s perception of innovative technology in a training context
influences his or her decision about accepting or rejecting the technology.
2. Individuals’ learning anxiety is intensified when using innovative technology
in a training context.
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3. Exposure to and early success in using innovative technology are essential to
the individual’s continued use of it in a training context.
4. Individuals must experience the utility of innovative technology to continue
using it in a training context.
5. Role models play a key role in individual’s continued use of innovative
technology in a training context.
6. An individual’s digital personality does not appear to influence technology
use in a training context.
Table 4 describes the essence and contribution of each conclusion. Each conclusion is
discussed below in detail.
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Table 4
Summary of Six Conclusions of the Study
Conclusion
Essence
Contribution
1.
The professionals experienced a progression of perceptions as
they used innovative technology in a training context. These
perceptions influenced their decision to continue using the
technology.
This new contribution addresses a gap within the extant
literature: the influence of individuals’ perceptions of
technology based on their experiences with the
technology and the impact the perceptions had on their
decision to continue using the technology.
2.
Individuals experienced increased learning anxiety as they
began to learn and use the innovative technology.
This is a new contribution that explains how learners
experience increased learning anxiety and its influence.
3.
Activities that allowed the individuals to experience early
successes (i.e., accomplish simple, relevant training tasks) with
the innovative technology provided the individual with the
motivation to continue the use of the technology.
4.
5.
6.
This is a new contribution because it explains the
significance of individuals’ experience with the
innovative technology and the importance of the
placement of activities that fosters this experience.
This is a new contribution because it explains the
When an individual used an innovative technology in a training
significant impact that individuals’ exposure to
context to attain his or her learning goals (i.e., utility), he or she
innovative technology. The role of exposure to the
will continue using the technology in the training context.
technology is not addressed in the extant literature.
This is a new contribution to the technology acceptance
Role models played an influential role in an individual’s
literature because it defines the role models’ (e.g.,
continued use of innovative technology in a training context by
instructors, technologically savvy peers, etc.) role in an
assisting the participants in discovering the utility and easing
individual’s acceptance of the technology in a learning
their learning anxiety.
context.
This challenges the popular assertion that age or
Exposure, not digital personality, influenced the continued use
generation is an indicator of an individual’s willingness
of innovative technology.
to accept technology. This is consistent with some
technology acceptance literature.
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Conclusion #1. An Individual’s Perception of Innovative Technology in a Training
Context Influences His or Her Decision About Accepting or Rejecting the
Technology
The first conclusion of this study is that an individual’s perception of innovative
technology in a training context influences his or her decision about accepting or
rejecting the technology. Figure 4 provides a graphic representation of the progression
of emotions experienced by the professionals in this study as they used innovative
technology in a training context. The participants’ experience began with a feeling of
awe and amazement and quickly changed to anxiety as they encountered the technology
in context, realizing that their performance in the training would be, at least in part,
contingent on how well they used the unfamiliar, innovative technology. However, as
the individuals’ exposure to the technology increased and they experienced successes
with the technology in context, their confidence grew and they became more
comfortable with the technology. The consistency of this progression of emotions
among the participants was greatly unexpected.
The participants used words such as “wow” (Juan, Q4T25; Teresa, Q2T13) and
“impressed” (Everett, Q1T7; Juan, Q4T25) to express the awe and amazement as they
saw the technology as they entered the classroom. While awe and amazement were the
initial impressions of the participants, they appear to have left a lasting, positive
impression on the training participants. These observations allowed the professionals in
this study to form lasting, favorable opinions of the technology. These opinions appear
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to have carried the participants through the later challenges of using the innovative
technology in context.
Figure 4. A progression of the individuals’ perceptions of technology
This consideration of the impact individuals’ perceptions have on their decision
to accept or reject technology is a new contribution to the technology acceptance
literature. As reported in Chapter II, the Unified Theory of Acceptance and Use of
Technology (UTAUT) (Venkatesh et al., 2003), suggested that a primary determinant of
technology acceptance is an individual’s perception of the technology’s ease of use.
Specifically, if an individual feels that the technology is easy to use, he or she is more
likely to use it. It is equally plausible to expect that an individual would likely
discontinue the use of the innovative technology if he or she experienced it and found it
difficult to use. However, neither UTAUT (Venkatesh et al., 2003) nor channel
expansion theory (Carlson, 1995; Carlson & Zmud, 1999; D'Urso & Rains, 2008;
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Germonprez, 2002) take into account the impact of emotions such as awe, anxiety, or
comfort on the users’ perceptions of ease of use.
Given the influence of the individuals’ perceptions on accepting the technology,
instructional designers must ensure that training courses do not require the training
participants to do too much too soon with the technology. Moreover, care must be taken
to ensure that training participants are properly and adequately equipped with the
knowledge and skills to use the innovative technology in the training context.
Conclusion #2. Individuals’ Learning Anxiety is Intensified When Using
Innovative Technology in a Training Context
The second conclusion of this study is that an individuals’ “learning anxiety”
(Schein, 1996) is intensified when using innovative technology in a training context. As
reported in Chapter II, Schein (1996) suggested that this “learning anxiety,” or a
restraining force that occurs when a learner encounters valid and relevant data that
challenges what was once held to be true, is expected in learning environments. As
indicated by Figure 4, the professionals reported that their perceptions of awe and
amazement quickly gave way to anxiety as they began using the innovative technology.
Specifically, the professionals’ anxiety appears to be stimulated by the use of the
technology, especially as they were learning to use it. As reported in Chapter IV,
participants used terms such as “vulnerable” (Everett, Q2T13), “apprehensive”
(Terrence, Q2T17), “cumbersome” (Rusty, Q4T15), and “frustrating” (Teresa, Q2T10a)
to express the anxiety they experienced. The participants’ detailed description, coupled
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with their body language while they were recounting the experience, clearly
demonstrated that this anxiety was beyond the typical learning anxiety.
This is not surprising when considering that the learning taking place is two-fold.
First, professionals are learning the content of the training course that often challenges
their beliefs. Secondly, the participants are also learning to use the innovative
technology, which may also be a change from the typical learning style. This is, at
minimum, an increase in the individuals’ learning anxiety.
If action is not taken to mitigate this anxiety, the use of innovative technology
could very well stand in the way of the individual learning the material central to the
training; therefore, the learning anxiety can (and should) be mitigated. Strategies can be
employed by training professionals to mitigate the intensified learning anxiety.
In this chapter, I will discuss two such strategies that the findings have shown to
be effective in mitigating the learning anxiety: creating activities that allow individuals
to experience success using the technology in context and employing instructors as
change agents and opinion leaders.
Conclusion #3. Exposure to and Early Success in Using Innovative Technology Are
Essential to the Individual’s Continued Use of it in a Training Context
The third conclusion addresses the importance of an individual’s exposure to the
innovative technology in a training context as he or she identifies the ease of use, or “the
degree of ease associated with the use of the system” (Venkatesh et al., 2003, p. 450).
While this may appear to coincide with the technology acceptance emphasizing the
significance of the ease of use literature presented in Chapter II (F. D. Davis, 1986,
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1989; F. D. Davis et al., 1989; Venkatesh et al., 2003), the emphasis of this conclusion is
based on the actual experience of individuals and not their perceptions of a future
experience. Moreover, the extant technology acceptance literature fails to adequately
explain how users of technology are to discover the ease of use. The findings from this
study provides some insights.
The findings presented in Chapter IV clearly indicated that the participants’ firsthand experience with the technology is a powerful tool in discovering the technology’s
ease of use. By using the innovative technology, participants in this study were able to
gauge the difficulty of using the technology and weigh that difficulty against the level of
investment that they were willing to make to learn the technology. As they were further
exposed to the technology, they described what they had previous identified as the cause
of their anxiety as “user friendly” (Juan, Q2T16), “intuitive” (Bobby Q1T1), and
“convenient” (Teresa, Q4T18). They cited the opportunities they were given to use the
technology in context and the subsequent successes they experienced as a primary
reason for their evolving comfort with the technology. These successes, although they
are comparatively small, appeared to serve as motivators for the participants as they used
the innovative technology.
These findings led to the next conclusion of this study: participants’ exposure
and early success while using the innovative technology are essential to the individual’s
continued use of innovative technology in a training context. This conclusion is new
information because the value of positive experiences with the technology is not clearly
addressed in the extant literature.
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This is important for instructional developers because it identifies the importance
of designing activities early in the course that encourage use of the innovative
technology in context. Moreover, this conclusion indicates that activities placed early in
a course must be designed to allow training participants the opportunity to enjoy
successes. Additionally, these activities should occur early in the training before the
training participants’ skills using the technology are tested.
Conclusion #4. Individuals Must Experience the Utility of Innovative Technology
to Continue Using it in a Training Context
The fourth conclusion of this study asserts that individuals must experience the
utility of innovative technology to continue using it in a training context. As discussed
in Chapter II, the UTAUT (Venkatesh et al., 2003) claims that a user’s perception of the
technology’s utility is an important predictor of an individual’s acceptance of the
technology; however, the literature does not discuss how individuals discover this utility.
My findings support the assertion in the extant literature that the individual’s
understanding of a technology’s utility is important to predicting an individual’s
acceptance of technology (F. D. Davis, 1986, 1989; F. D. Davis et al., 1989; Venkatesh
et al., 2003). However, my analysis of the findings presented in Chapter IV go further
than the aforementioned technology acceptance literature by proposing that individuals
must experience the utility of the innovative technology to continue using it in a training
context. In other words, the findings in Chapter IV indicate that an individual simply
being told about the utility is not enough for their acceptance; they must experience the
technology’s utility to continue using it.
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This conclusion provides insight into the design of training using innovative
technology. This assertion that utility must be experienced by the training participants
makes a strong case for experiential activities showcasing the technology’s capability to
assist individuals in attaining their training goals. This also means that the innovative
technology in training must have a purpose focused on improving the participants’
performance in the training.
Conclusion #5. Role Models’ Play a Key Role in Individual’s Continued Use of
Innovative Technology in a Training Context
The analysis of the experiences of professionals interviewed for this study have
identified many facilitators who can potentially influence the individuals’ continued use
of innovative technology in a training context, including (a) relevant content, (b) a solid
course design, and (c) adequate preparation of the technology used. However, the
participants in this study have consistently identified role models (whether instructors or
their peers), as key to their continued use of the technology.
In Chapter II, role models (Schein, 1996) were described as having two possible,
but distinct roles in facilitating change: (a) a formal role or “change agents” (Rogers,
2003, p. 27) and (b) an informal role or “opinion leaders” (Rogers, 2003, p. 27). Clearly,
instructors are placed in a formal role of authority with the intention of facilitating
change “in a direction deemed desirable” (Rogers, 2003, p. 27) by the organization.
However, in many cases, when instructors are members of the same social system as the
professionals and have a higher technical competence, they can function as an opinion
leader.
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As a change agent in a training context, instructors guide participants to use the
innovative technology to accomplish learning goals. In other words, the instructor-aschange-agent should be able to close the deal on the use of the innovative technology
with the participants in the training context. Instructors are able to accomplish this
through teaching and coaching the participants on the use of the innovative technology.
As an opinion leader, the instructor is uniquely positioned to influence the
participants to continue using the innovative technology based on their membership in
the same social system. He or she is able to influence the course participants as peers by
mentoring them. In each role, the instructors are able to encourage and persuade the
participants by demonstrating the ease of use and assisting the participants in finding the
utility of the innovative technology.
This conclusion is important because it identifies role models, whether as opinion
leaders or change agents, as influential to the individuals’ decision to continue using
technology. Instructors are uniquely positioned to facilitate change, mitigate and even
alleviate the participants’ anxiety, and help the training participants identify the ease of
use and utility of the innovative technology. This puts the instructor in a very powerful
position and makes him or her an important part of ensuring technology acceptance.
Given this, training managers must ensure that instructors who use innovative
technology are well prepared to use the technology. Otherwise, instructors can dissuade
individuals by showing their incompetence with the technology.
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Conclusion #6. An Individual’s Digital Personality Does Not Appear to Influence
Technology Use in a Training Context
The final conclusion of this study addresses the popularly held belief that an
individual’s generation or age influences his or her willingness to accept an innovative
technology (Palfrey & Gasser, 2008; Prensky, 2001b, 2001c; Tapscott, 2009). This
belief proposes that individuals of recent generations (e.g., Generation Y), the people
Tapscott (2009) calls “Net Geners,” will accept innovative technology willingly. As
Tapscott (2009) states, “young people just breathe it in” (p. 19).
There is no evidence from this study to support that age or generation provided
any influence to participants’ decisions to use the technology. In fact, findings from this
study suggest quite the opposite. All of the participants continued to use the innovative
technology despite their initial anxiety; only one participant was part of the younger
generation. To add to this, the lone member of Generation Y interviewed for this study
admitted:
It wasn’t the same as having a hard copy in your hand. I like to have the feel of a
book in my hand. I can flip to whatever page I need. I can make notes. You
can’t really do that with an iPad. If you do, you have to open up a little make-anote-about-this thing and it’ll mark it, but it’s not the same as being able to just
look down and see what you’ve written. So, it was a little frustrating…In the
courses I took after that [first training course], I just didn’t use it. I stopped using
it pretty much except for pictures. …It was kind of pointless. (Teresa,
Q2T10a&b)
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This final conclusion is significant to training professionals because it begins to
dispel the myth that one generation is predisposed to accepting technology. As a result,
training designers and instructors should proactively seek effective instructional
techniques to facilitate adoptive strategies, rather than assuming technology would be
automatically accepted by a younger audience.
A New Conceptual Framework
As presented in Chapter II, the UTAUT (Venkatesh, 2003) is an analysis and
distillation of eight different theories and models related to technology acceptance that
presented a common framework including a three-step process that explained technology
acceptance. The steps of this process are (1) the individual’s reaction to using
technology, (2) an intention to use the technology, and (3) the actual use of the
technology (Venkatesh et al., 2003). Similarly, Rogers (2003) presented a five-step
innovation-decision process explaining how social systems adopt or reject innovation.
The stages in this process are (1) knowledge, (2) persuasion, (3) decision, (4)
implementation, and (5) confirmation. In addition to the adoption of technology and
innovation, Schein (1996) broadened Lewin’s three-step change model to explain
learning as change. I applied these processes and models in this study to provide a
conceptual framework of individuals’ experience when encountering and accepting
innovative technology in training applications. However, these theories and models did
not adequately explain the process of adaptation and adoption described by the trainees
who participated in this study.
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For example, the technology acceptance process outlined in the UTAUT
(Venkatesh et al., 2003) and the technology acceptance model (F. D. Davis, 1986, 1989;
F. D. Davis et al., 1989) explain the phenomenon of technology acceptance from a
predictive perspective. In other words, the UTAUT and other technology acceptance
literature focused on identifying the determining factors of technology acceptance.
However, the literature did not examine technology acceptance as a phenomenon of
change and, therefore, failed to explain or anticipate the anxiety described by the trainees
in this study.
Additionally, the UTAUT included Moore and Benbast’s (1991) adaptation of
Rogers’s diffusion of innovations as part of the meta-analysis. However, it failed to
include certain factors that are critical to the diffusion of innovations (i.e., the role of the
change agent, the role of the diffusion networks, and innovator and adopter categories)
(Rogers, 2003). In addition, the UTAUT does not provide a process that describes how
change occurs as individuals encounter and decide whether to accept or reject an
innovation.
On the other hand, Rogers’s diffusion of innovations does provide a strong model
that explains individuals’ experience as an innovation is adopted throughout a social
system. Rogers (2003) also identifies factors that are important to the adoptions and
institutionalization of an innovation, such as (a) the role of the change agent, (b) the
significance of the channels in which the innovation is communicated within a social
system, and (c) the characteristics of the adopter. Finally, Rogers provides five
attributes of innovations that can be used to identify the adoptability of the innovation.
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However, Rogers’s innovation-decision process ends when the innovation is
institutionalized within the social system. While institutionalization is appropriate when
the innovation will be used beyond the classroom, it is not appropriate in cases when
institutionalization of the innovation is either not the goal or not likely. This is the case
when innovative technology is used to facilitate training.
Rogers (2003) also presented two separate roles for change agents: the change
agent (a confederate to the organization seeking the desired change) and the opinion
leader (an informal influencing position). As mentioned earlier in this chapter, these
roles reflect the instructors’ role in the shared experiences of the participants in this
study.
The six conclusions presented in this chapter are based on the experiences of the
public safety professionals participating in this study and showed a pattern of actions and
reactions of the participants as they used the innovative technology. I have taken this
pattern of actions and reactions and developed a conceptual framework to explain the
experience of public safety professionals as they use the innovative technology. Figure
5 provides a graphic representation of the professional’s actions and reactions, as well as
possible points where role models can intervene. This framework has points of
connection with the extant literature and also provides insight into the order of
experiences leading to a decision to accept or reject the technology. Each stage of the
model is described below.
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Figure 5. A new conceptual framework that illustrates the process experienced by
individuals encountering innovative technologies.
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Stage 1: Excitement
This introduction may occur before trainees ever enter the classroom or well after
they have started the training. In addition, the introduction may range from word of
mouth from previous participants, to a simple unveiling of the technology or a detailed
demonstration of the technology’s capabilities. A key point is that the beginning of this
stage is unpredictable and may already be in progress when trainees actually enter the
classroom or encounter the technology.
In this stage, trainees are briefly introduced to the technology and will likely
experience the feeling of awe and amazement. This corresponds with the awe and
amazement described in Conclusion #1. These feelings are likely resulted by the
anticipation of using the innovative technology. However, these feelings may be based
on false expectations created by inaccurate or incomplete information.
At this stage, trainees do not actually interact with the technology. In this stage,
it is likely they obtain inadequate information about the innovative technology through
sources such as course advertisements and previous training participants. This stage is
similar to Schein’s (1996) disconfirmation and Rogers’s (2003) knowledge stage.
Stage 2: Anxiety
As a result of the incomplete information and little or no interaction with the
innovative technology, trainees experience varying levels of anxiety that can manifest in
ways such as frustration, anger, confusion, loss of self-esteem, and even a loss of selfefficacy. The intensity of this is likely to be in direct proportion to the perceived threat
to the individual created by the change. For example, if the trainee perceives that
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accepting the innovative technology is a great threat to his or her identity or self-esteem,
the intensity of the anxiety may be greater. This anxiety, similar to Schein’s (1996)
learning anxiety, can lead trainees to resist the innovative technology if it is not
mitigated.
Stage 3: Interaction With the Technology
In this stage, trainees are given an opportunity to interact with the technology
first hand. This allows them an opportunity to confirm or disconfirm the information
already provided in the previous stages. Additionally, trainees are able to begin
gathering data that will later inform their technology acceptance decision. This stage
should be part of the training instruction and facilitated by instructors who may perform
as opinion leaders, change agents, or in both roles.
To aid in facilitating this stage, training activities in this stage should be designed
to communicate information so that trainees are able to familiarize themselves with the
technology. This stage should also allow trainees opportunities to gain some initial
experience with the technology; therefore, context is important. Providing trainees
opportunities to experiment with the technology in the same or similar context to how it
is used in the training will likely lead trainees to form their own positive opinions and
beliefs about the technology. In addition, instructors should allow time for
experimentation with the technology. These activities are essential in selling the
innovative technology; this should not be taken lightly.
The role model intervention. The role models, whether functioning as opinion
leaders or change agents, are important to facilitating training experiences and
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influencing the technology acceptance decision. As previously mentioned, instructors
are often placed in the role of a change agent or, at minimum, an opinion leader. In
these roles, instructors are uniquely positioned to make a moderating influence against
the aforementioned learning anxiety and can reduce or eliminate the resistance to the
technology as a result of the learning anxiety. To do this, instructors must be capable of
coaching and mentoring trainees as they use the technology. While this is particularly
important in the early stages of the process, instructors must be prepared to perform at
any stage throughout the training to prevent disconfirmation.
Stage 4: Usability Evaluation
The usability evaluation stage begins once trainees have had opportunities to
interact and become familiar with the innovative technology. In this stage of the
process, the trainees continue to gather data about the technology that will inform their
decision to accept. There are two types of data that are gathered: utility data and ease of
use data. Utility data is information that signals to trainees that the innovative
technology will assist them in improving their performance. Ease of use data is
information that demonstrates to trainees that using the innovative technology would be
relatively free from effort and that they can effectively use it.
Trainees gather this information and make judgments about their ability to use
the technology to accomplish the goals of the training. This is the probable location
where Schein’s (1996) concept of cognitive restructuring occurs. As the data are
gathered and processed, trainees are redefining what they previously understood,
including their abilities to perform with the technology.
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It is important to note that learning anxiety is likely to occur in this stage,
especially if there is a threat to the trainees’ self-esteem or self-efficacy in the classroom.
If learning anxiety occurs and is not moderated by the instructors or other opinion
leaders (e.g., other trainees), then there is a possibility that the trainees will reject the
innovative technology; however, if the trainees identified the technology as an
enhancement to their performance and observed that the technology is relatively easy to
use, then the likelihood the innovative technology is accepted is increased.
Stage 5: Decision to Accept
At this stage of the process, the trainee has gathered and processed the usability
data and must now make a decision to reject, partially accept, or fully accept the
technology being used in the training. Rejection occurs when the trainee rebuffs the
technology used in the training. This often results in the trainee disengaging from the
training. In fact, rejection may occur before a participant ever enters the classroom,
meaning that the trainee does not attend the training. Rejection of the technology may
manifest in the form of the trainee leaving the classroom, taking on tasks that are devoid
of the technology, or engaging in disruptive behaviors to avoid the technology. It can
also manifest as the trainee stating that he or she will not use the technology or intensely
criticize the technology. While none of the participants in this study appeared to reject
the technology used in their training, it does occur (as other studies reveal). Rejection of
the technology terminates this process.
Partial acceptance occurs when the trainee uses the technology, but requires
additional exposure to the technology and/or more interaction with the role model(s).
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The trainee has made a tentative acceptance of the technology, but could still reject the
technology if his or her needs are not fulfilled. When partial acceptance occurs, the
trainee may still be hesitant to engage the technology on his or her own or continue to
require a significant amount of coaching. When partial acceptance occurs, the trainee
will seek out more exposure to the technology and repeat the usability evaluation to
confirm his or her understanding of the technology’s utility. This will recur until either
the trainee decides to fully accept or reject the technology or the use of the technology is
no longer required.
Full acceptance occurs when a trainee embraces the technology without further
anxiety. He or she may not use the technology error-free, but the trainee is willing to
engage the technology without reservation. When full acceptance occurs, the trainee
advances to the next stage: acceptance.
The decision point varies based on the individual. The participants in this study
indicated that the decision stage often takes place early in the training evolution.
Moreover, there is not a single indicator that the decision stage has begun or ended.
Perhaps the most expected visible sign is that the trainee is using the innovative
technology; however, this can be deceiving because trainees may still be in the
interactive stage or usability evaluation stage.
Stage 6: Acceptance
Acceptance is the last major stage in the process; however, because
institutionalization of the innovative technology is unlikely, the process may not end
with this stage. Acceptance begins once the individual decides to accept the innovative
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technology and he or she decides to use the technology to its fullest extent. This stage
continues as long as the innovative technology is used in the training.
Trainees continue to receive and process the two previously mentioned types of
data, utility and ease of use, to reinforce their decision to accept the technology.
However, in this stage, information may be presented that challenges the trainees’
beliefs about the innovative technology. When this occurs, the trainees are likely to
enter a period of re-evaluation or seek reconfirmation of their decision. To accomplish
this, data are gathered and processed and the trainees repeat the usability evaluation and
decision stages until they reconfirm their decision to accept or, in some cases, reverse
their decision. If the decision is reversed, the innovative technology will be rejected.
The instructor, as a change agent, has a significant role in moderating the effects
of this disconfirming information and mitigating the potential rejection. To be effective
at this, the instructor must be capable of recognizing the trainee’s learning anxiety,
which will often manifest as frustration, confusion, or apprehension. When this is
identified, the instructor must intervene as necessary to answer questions and mitigate
the anxiety to prevent reversal of the acceptance decision and the subsequent rejection of
the innovative technology.
In summary, this section has presented a new conceptual process, illustrated by
Figure 4. This model explained the experiences of trainees as they encountered and
decided to accept innovative technology. I constructed the model based on the
experiences of the trainees who participated in this study. The conceptual process
explained what trainees experience as they encounter innovative technology used in a
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training course. The process identifies points where instructors, acting as opinion
leaders and/or change agents, are able to intervene to facilitate the trainees’ acceptance
of technology.
In addition, this process identifies areas in the design of training where
instructional designers and training mangers can build activities to allow training
participants opportunities to experience the utility of the technology as it enhances their
performance in the training course. This conceptual framework offers a unique lens to
conceptualize the trainees’ experience as they encounter innovative technology. It is
informative and helpful to instructional designers, training managers, and instructors
who develop training that uses innovative technology.
Researcher’s Reflection
The Impact of My Biases
As mentioned in Chapter III, I recognized several sources of my potential bias:
my long and vast experience as a first responder; my professional experiences as an
instructor and developer of training, and my status as a self-proclaimed techno-geek.
Throughout the dissertation research process, I have reflected on how these potential
biases may have impact my understanding and interpretations of the participants’
experiences as they encountered the innovative technology. In what follows, I have
attempted to acknowledge these impacts.
I have had a career as an emergency responder with more than 25 years spread
between emergency medical services, emergency management, and the fire service.
While this experience uniquely positioned me to understand the nuances of the
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experiences of emergency responders, it has also come with a bias: I held an archetypical
image of these emergency responders. Early in the research process, I recognized that I
was somewhat star-struck by some of the participants in this study because of the
departments they came from or the positions they held; and in some cases, both. I
recalled a specific experience where the words of one participant during an interview left
me reeling. After the interview, I reflected on my thoughts and reactions and quickly
realized that my expectation for this archetype was actually a bias. From that point, it
became clear that I had to view each person as an individual, and not an idealized vision
of a firefighter or police officer. I also had to keep myself in check against assuming too
much about the commonality of my experiences as an emergency responder and the
participants’ experiences. So, while I found it easier to empathize with these participants
in terms of the responsibilities and pressures of being an emergency responders and
having a solid understanding of the job, that was the extent of our common experiences.
In a second example, as a professional instructor and more so as the architect of
one of the courses involved in this study, I had to ensure that my biases, pro or con, did
not outweigh or overpower the experiences of the participants. For example, I held fast
to my belief that as an instructor and training designer, we must build training to be
student-centered, not instructor or organization centered. This belief was a foundation of
this study and has continued to frame many of the conclusions by defaulting to what is in
the best interest of the training participant, not the instructor or organization. As a
qualitative researcher, instead of separating myself from my own biases and beliefs
(Annells, 2006; Groenewald, 2004; Moustakas, 1994; Ruona, 2005; van Manen, 1990).
162
I acknowledged them and subsequently used several techniques to keep my biases in
check and to ensure the findings reflected the participants’ experiences rather than mine.
Finally, as a self-proclaimed techno-geek, I have had many experiences using
new and innovative technologies, as well as designing and implementing innovative
technologies in training courses. In other words, I consider myself a believer in the
value of technology in training. Therefore, a major bias I carried to this study was my
desire to reveal success with the technology in the training context. Again, I must
acknowledge that I was an architect of one of the courses and had some influence over
the design of simulation used in this study. In fact, many of the participants in this study
knew of my involvement in the course design and the development of the simulation.
Because of this, some recognized me as an expert in the use of simulations and / or
instructional design. Therefore, I had to take great care to ensure that the conclusions of
the study were derived from the lived experiences of the study participants rather than
my desires or expectations.
Contradictions
In addition to the impact of my biases, I have had a great deal of reflection on the
differences that existed between what the participants said and what they apparently
meant. As mentioned in Chapter III, the video recordings provided a unique opportunity
to observe contradictions between the words they spoke were and the emotions they felt.
For example, at one point, Terrence stated, “I was not scared of it [the technology]…”,
yet as I reviewed the video, it was clear that Terrence was very uneasy as he recalled the
163
experience. This was an example of several events that took place throughout the
interviews.
The video recordings provided a way to gain a deeper understanding of the
experiences of these professionals that only the words from the transcriptions could not
provide. As I watched and reflected on the video recordings, I was able to see more and
more that opened many avenues to gaining a deeper understanding of the participants’
experiences. As I worked through de-conflicting these apparent contradictions, the task
led to a greater understanding of the participants in the study and myself. In some cases,
the participants were saying things that would allow them to save face, but their body
language would betray their words. In the end, this exploration brought greater meaning
to their words and led me to the six conclusions mentioned earlier in this chapter. The
lesson in this is that the words cannot always be taken at face value to completely
understand the meaning.
Recommendations for Practice
Including technology in training provides opportunities for instructors to enhance
the training experience and address the aforementioned expectation of “edutainment”
(Junginger, 2008, p. 20); however, there must be a clear purpose behind the technology
and a solid understanding of how professionals perceive technology in a training context.
Too many times, a great idea was generated before its time and discarded after much
expense and effort. An unstated intention of my study was to provide practitioners with
some insight into the extent to which technology has been accepted in training. While
this study is one of several that has examined the issue of technology acceptance, it is
164
different from most of the existing studies because it examines the issue from a unique
context: technology used in training. Consequently, this study offers several useful
implications for training practitioners, specifically training managers and instructional
designers. In the following section, I discuss these major implications.
Understand That Participants Will Be Anxious About Using the Technology and
Address It
For practitioners, it is important to recognize the psychological factors in play
with learning and also with the introduction of what may be, in essence, foreign.
Instructional designers, instructors, and training managers must all be proactive in
anticipating and addressing the anxiety that may arise as a result of using the technology.
Several strategies can be employed to mitigate the anxiety. First, instructional designers
and training managers need to ensure that courses contain adequate and accurate
information on any innovative technology they intend to use in the training. The
technology must be well understood before it is used in the training. This means that the
training program must be designed in a way that it incorporates meaningful applications
of technology. Moreover, activities should be provided early in the training evolution so
that the training participants are able to (a) gain experience with the innovative
technology and (b) experience the utility of the technology.
Second, because the introduction stage may begin well before the course, precourse information should include information on the innovative technology used so that
potential trainees can develop an initial understanding of the technology before they
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arrive in the classroom. This information should clearly describe the innovative
technology and explain how it is used.
A change agent that is incapable or unwilling to support the change (i.e., the
innovative technology) can do a large amount of harm to the technology acceptance
process. Therefore, a third strategy that can be employed is to ensure that the training
staff is properly prepared to be opinion leaders and/or change agents. Given the critical
role of instructors as authorities in the course and the likelihood that they will be opinion
leaders and/or change agents, they should have a firm grasp on how to use the
technology and an ability to teach others how to use it. Training managers must ensure
that they give adequate initial training on the use of the technology to the instructors.
Additionally, training managers must also ensure that instructors are kept up to date as
the innovative technology changes.
Let Them Experience the Utility: Provide Meaningful Opportunities for
Participants to Interact With the Technology in a Training Context
Training managers, instructional designers, and instructors must take actions to
ensure that the course involves activity using the innovative technology in a meaningful
way to the trainees, rather than a frivolous activity or lessons in abstraction that do not
demonstrate the technology’s potential utility.
While it is near certainty that multiple digital personalities are likely to be
represented in most training audiences, evidence from this study suggests that this is not
a factor in an individual’s decision to use technology. Instead, the evidence suggests
that factors such as exposure to the specific technology, support from the individual’s
166
social network, and prior experiences with technology in general have a greater impact
on a decision to accept technology than a person’s digital personality. More importantly,
age is nothing more than a coincidence. It is also important to understand that an
individual’s digital personality is not fixed; it evolves as the factors change. Just as
individuals have varied personalities over time, their digital personality may change as
their experiences and circumstances change. This study has demonstrated that
assumptions about an individual’s abilities based on age, socioeconomic status, or
perceived digital personality are often inaccurate. Acting upon these assumptions is
likely to ultimately increase a trainee’s anxiety and risk rejection of the innovative
technology.
In addition, trainees’ interaction with an innovative technology is important to
their acceptance or rejection of the technology. Failing to provide trainees with
meaningful opportunities to determine the innovative technology’s utility are
opportunities lost for acceptance. As noted previously, activities providing these
opportunities are critical to informing the trainees’ as they are preparing to make a
decision about the technology. Therefore, instructional designers must construct and
instructors must dutifully carry out activities that allow the innovative technology to be
used, preferably in context, so that the utility of the technology can be experienced by
trainees. These activities should begin with preparing trainees to use the innovative
technology in the training. They should also explain the functionality and provide
examples of how the technology would be used in the training.
167
As the training progresses and the innovative technology is being used to
facilitate the training, the instructional staff should coach and mentor trainees as needed.
Activities must be designed to ensure that the technology is capable of effectively
supporting the activity. For example, an activity should not require a color display if the
technology is only capable of displaying black and white on the screen.
Avoid Distractions: Do Not Use Technology for Technology’s Sake
Using technology in training to showcase the technology, without ensuring that
the technology adds value to the learning is using technology for technology’s sake. The
use of technology simply for the sake of using technology is a death nail resulting in
distractions, failures, and ultimately a serious threat to acceptance of the technology.
Incorporating innovative technology in training activities must be a thoughtful and
carefully planned process. Training managers, instructional designers, and instructors
must all take care to ensure that the technology both serves a purpose in the training and
enhances the training. If the technology becomes a distraction, the training should be
modified to remove the distraction, including removing the use of the technology if
necessary. Training professionals must ensure that learning, not the technology, is the
central focus of the training.
Recommendations for Research
I adopted a naturalistic, hermeneutic phenomenological research approach in this
study adopted. This approach provided the basis to collect rich and descriptive data;
however, this methodology does not allow the findings to be generalized to a larger
population (Patton, 2002).
168
More studies are needed to examine the topic from other methodological
standpoints. Studies conducted using a grounded theory, ethnographic, and other
approaches can deepen our understanding of this phenomenon. For example, a critical
perspective on technology acceptance is an important lens that appears to be missing
from the current research. Some authors have written on the use of technology from a
critical approach (Callahan & Sandlin, 2007; Gabriel, 2008); however, few empirical
studies have taken a critical perspective to explore the phenomenon of professionals
using technology in a training context from a critical perspective. The critical paradigm
will be valuable in that it has the potential to address issues such as the impact of the
digital divide, which has been largely overlooked in literature.
Due to time and financial constraints, the study was bounded to a specific set of
criteria. First, this study focused on six public safety professionals with varied levels of
experience. Future research should include a broader selection of professionals to gain
additional insight into this phenomenon. In addition, the public safety professionals in
this study were limited to law enforcement and the fire service. These participants were
not broadly diverse in terms of their subject matter expertise. Research that examines
the experiences of other professionals using innovative technology in a training context
would provide additional empirical evidence to enrich the understanding of trainees’
experiences as they use innovative technology.
This study focused primarily on highly experienced professionals who were wellestablished in their field and attending advanced training. So far few, if any, studies
have have focused on entry-level trainees. Therefore, I suggest future studies should
169
focus on entry-level professionals to gain an understanding of their experiences. Other
future studies can compare trainees at both levels to identify common and different
experiences.
Another limitation of this study was the exclusive focus on innovative or
emerging technology. As stated previously, there has been little exploration of this
phenomenon of professionals using technology in training contexts. The focus of this
study was specifically on professionals’ experience as they use innovative or emerging
technology in a training context; however, there is little research on the experiences of
professionals using any technology in a training context. As a result, there is little
information to allow comparison of experiences with different types of technologies.
In addition, researchers (e.g., Rahim & Finch, 2011; Saeed, Yang, & Sinnappan,
2009; Zuckweiler & Cao, 2009) have shown that individuals with certain learning styles
are more receptive to the use of technology in learning environments. Findings from this
study did not provide any evidence to support or challenge this belief. Future research
should explore the relationship between individuals’ learning styles and their experience
with innovative technology, including examining if certain learning styles are a
determinant of an individual’s acceptance of an innovative technology. Findings in this
regard would facilitate learner-oriented instructional design.
In this study, I constructed a new conceptual framework based on the experiences
of six public safety professionals using innovative technology in a training context.
More empirical studies, are needed to test the validity and reliability of this framework.
For example, Rogers (2003) diffusion model addressed the concept of discontinuance.
170
Rogers (2003) defined discontinuance as “a decision to reject an innovation after having
previously adopted it” (p. 190). This phenomenon occurs when an innovation is
superseded by a different (often newer) innovation or when the user becomes
disillusioned with the previously accepted innovation. This phenomenon was not
illuminated in this study; however, developing an understanding of this phenomenon
will provide a better insight into why individuals reject an innovative technology as well
as what to do when this occurs.
Conclusion
The purpose of this research study was to explore the phenomenon of public
safety professionals using innovative technology in a public safety training context to
better understand their experiences as they used innovative technology in a training
context. A single question guided this research: What is the experience of public safety
trainees who are required to use innovative or emerging technology in face-to-face
training?
I employed a qualitative, hermeneutic phenomenological research approach to
conduct this study. This approach used in-depth interviews with six public safety
professionals with open-ended questions and supporting data from observation and
documents to provide a contextual frame. Participants in this study were identified
through purposeful sampling focusing on public safety professionals who attended
training that incorporated innovative technology conducted in the United States.
Through an analysis of the findings of this study, I have developed six major
conclusions that were discussed in this chapter. These conclusions are:
171
1. An individual’s perception of innovative technology in a training context
influences his or her decision to accept or reject the technology.
2. Individuals’ learning anxiety is intensified when using innovative technology
in a training context.
3. Exposure to and early success in using innovative technology are essential to
the individual’s continued use of it in a training context.
4. Individuals must experience the utility of innovative technology to continue
using it in a training context.
5. Role models play a key role in an individual’s continued use of innovative
technology in a training context.
6. An individual’s digital personality does not appear to influence technology
use in a training context.
These conclusions provide several contributions to the body of literature
concerning this phenomenon. Specifically, two conclusions emphasize the influence of
an individual’s perceptions and the effect of learning anxiety on an individual’s use of
innovative technology, which has previously not been addressed in the literature.
Additionally, I have provided implications for human resource development
practitioners and researchers. For practitioners, the findings offer valuable information
that will potentially enable effective integration of innovative technologies in training.
The findings provide opportunities for researchers to explore the impact of different
technologies used on trainees’ technology acceptance process. Finally, the findings
172
provide a potential to develop new theories to explain how the acceptance of innovative
technology occurs.
In addition to the six conclusions, I presented a new conceptual framework to
describe the experiences of professionals using innovative technology in training
contexts. These conclusions and the conceptual framework provided unique
contributions to scholarship on the topic of technology acceptance. Each of these items
moves beyond simply identifying the determinants of technology acceptance and invites
an integration of multiple domains into one framework. Finally, this chapter concluded
with implications for both practice and additional areas for future research. These
implications included considerations for training managers, instructors, and instructional
designers.
As stated from the outset of this study, innovative technology is ubiquitous in
nearly every society. In this study, I examined the experiences of professionals in a
training as they used innovative technology. A significant result of this study was a
conceptual framework that described the professionals’ experiences of encountering
innovative technology. This conceptual framework can provide a foundation for a
theory of technology acceptance that will continue to inform training managers and
instructional designers on how to best incorporate innovative technology into training
courses.
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186
APPENDIX A
TEXAS A&M UNIVERSITY IRB APPROVAL OF RESEARCH
187
188
APPENDIX B
OBSERVATIONAL PROTOCOL
OBSERVATIONAL PROTOCOL
A Close Look at Technology Acceptance: A Phenomenological Study
Date:______________________________________________________________
Start time: _______________________ End time: ______________________
Location: ________________________________________________________
Setting / individual observed: _______________________________________
Observer: ________________________________________________________
Role of the observer (participant / Non-participant):____________________
DESCRIPTIVE
REFLECTIVE
189
APPENDIX C
INFORMED CONSENT FORM
Participant’s Informed Consent for Participation in the Research Study:
A Close Look at Technology Acceptance: A Phenomenological Study
By my signature on this form I acknowledge the following:
1.
My participation is voluntary, and I understand that I may choose to respond to any, all or none of
the questions asked in the individual interview session(s) or focus group sessions.
2.
I was informed that I may withdraw my consent to participate in the study at any time without
penalty by advising the researcher.
3.
I have been assured that my responses will remain strictly confidential with regard to my identity
4.
I am also aware that excerpts from the interview may be included in the thesis and/or publications
to come from this research, with the understanding that the quotations will be anonymous.
5.
I understand the research requirement that the individual interview session(s) and focus group
sessions are audio-taped and/or videotaped and that no identifying information will be associated
with individuals in the study.
6.
I understand that I will not receive any direct personal rewards from participating in this study,
and my participation will not affect my occupational or student standing.
7.
I understand that I will be given opportunity to review the transcribed audio/video taped
individual interview and focus group sessions of my comments and input before the transcripts
are finalized for analysis.
8.
I will have the opportunity of seeing the results of this study if I so request.
Participant signature _____________________________________ Date: __________________________
Printed Name:
Participant Email Address: _____________________________
Signature of person obtaining consent:
Date: _____________________________
Printed Name: ___________________________________________
Principal Investigator: Jason Moats_______
Phone number of PI:
979-324-9732
I request a copy of the research results be sent to me at the following address:
Any questions about this research may be directed to the Principal Investigator or Dr. Frederick Nafukho,
Department Head, Department of Educational Administration and Human Resource Development at
511DB Harrington Office Building, Texas A&M University, College Station, TX 77840, Phone: (979)
862-3395
Any questions regarding your rights as a research subject may be addressed to
the Texas A&M University Human Subjects Research Protection Program (979) 4584067 All research projects that are carried out by investigators at Texas A&M University
are governed by the requirements of the College and state and Federal government.
190
APPENDIX D
INTERVIEW CONFIRMATION EMAIL
Subject Line: Participation in Research Study
Dear ______________,
This email is an invitation for you to participate in a qualitative research study that I am
conducting as partial fulfillment of the requirements for obtaining a Doctor of Philosophy degree
from Texas A&M University. I would like to provide you with further information about this
project and what your involvement would require.
As you are aware, the emerging technology is increasing the capability of training organizations
throughout the United States and the world. It is my desire to study the experiences of training
participants, such as you, to better understand the decision-making process to accept technology.
Participation in this study is voluntary. It will involve at least one personal interview. Each will
session will be video recorded and last approximately 60 minutes. The interview will take place
in a mutually agreed upon confidential setting. Should you feel that more time is needed, we can
extend the time.
As a participant, you may decline to answer any of the interview questions, should you so desire.
You may also decide to withdraw from this study at any time without any negative consequences
by advising the researcher. The individual interviews will be video recorded to facilitate
collection of information, and later transcribed for analysis.
After each session, I will send you a copy of the transcribed conversations to give you the
opportunity to confirm the accuracy of our conversation and to add or clarify any points that you
wish. All of this information is considered strictly confidential, and your name will not appear
anywhere in my dissertation or in any written reports from the study. However, with your
permission and under a pseudonym, anonymous quotations from the interview and focus groups
sessions may be used in the written dissertation or reports.
Following the completion of the study, you may have the results sent to you upon request. All
data collected during this study will be retained for a period of three years in a locked file in my
office where one but me has access to it. There are no known or anticipated risks to you as a
participant in this study.
I would like to assure you that this study has been reviewed, and it has received approval from
the Institutional Review Board at Texas A&M University.
Thank you
Jason Moats
191
APPENDIX E
DEMOGRAPHIC QUESTIONNAIRE
A Close Look at Technology Acceptance: A Phenomenological Study
Instructions: Please provide the following information by filling in the blanks
Please provide your email
address
What best describes your
age
What is your current
profession
18-22
23-30
31-40
Fire Service
41-50
61-75
Law Enforcement
EMS
> 75
Other
If other, please describe
____________________________________________
How long have you been in
your current profession
How long have you used a
tablet (e.g. iPad, Kindle
Fire, Motorola Xoom, Nook
Color, etc)
How long have you used a
SMART Phone (e.g.
iPhone, Droid, etc)
How often do you currently
use a personal computer for
personal or business use?
How long have you played
console video games
(e.g. X-Box, Wii, Nintendo,
etc)
How many different
training courses have you
taken online
<1 yr
1-5 yrs
6-10 yrs
11-15 yrs
16-25 yrs
> 25 yrs
Never
< 3 mos
3-11 mos
12-24 mos
> 24 mos
Never
<3 mos
3-11 mos
12-24 mos
> 24 mos
Daily
3-4 / wk
1-2 / wk
<1/wk
Never
<6 mos
6-24 mos
25-48 mos
1-2
3-5
0
192
> 48 mos
>5
APPENDIX F
INTERVIEW PROTOCOL
Interview Protocol
A Close Look at Technology Acceptance: A Phenomenological Study
Date:_____________________________________________________________
Start time: ________________________ End time: ______________________
Location: _________________________________________________________
Interviewer: _______________________________________________________
Interviewee: _______________________________________________________
Role of the Interviewee: _____________________________________________
1. Please share your experience when you encountered a new or unfamiliar
technology used to facilitate a training course?
2. What were your feelings toward the technology as you were learning to use it?
3. How did you feel about your performance in the training as you were learning
and using the technology?
4. Reflecting on the use of the technology, what kind of reaction did you have after
initially using it?
5. In what ways has this experience of using technology impacted your experience
to using technology in other settings?
6. Based on your experience, what would you want someone to know as they
integrate new and/or unfamiliar technology in training?
193
APPENDIX G
DATA ANALYSIS SAMPLE SHEETS
194
195
196
APPENDIX H
VITAE
Jason Moats, CTT
911 McAshan St
Bryan, TX 77803
Phone: 979 324-9732
Email: jbmoats@tamu.edu
EDUCATION
PhD
Educational Human Resource Development, ABD
Anticipated graduation December 2013
Texas A&M University, College Station, TX
M.S.
Educational Human Resource Development, May 2007
Texas A&M University, College Station, TX
B.S.
Workforce Education and Development, May, 1997
Specialization in Education and Training Development
Southern Illinois University – Carbondale, Carbondale, IL
A.S.
General Studies, December 1996
Vincennes University, Vincennes, IN
MAJOR RESEARCH AREAS AND INTERESTS
Understanding the integration of emerging and innovative technology in training to improve
performance; understanding factors that improve performance in organizational training
interventions (learning transfer and knowledge retention); identifying and exploring the role
of human resource development in homeland security; exploring the role of human resource
development in crisis management;.
INDUSTRY EXPERIENCE
Program Director, Emergency Services Training Institute, Texas A&M Engineering
Extension Service, Texas A&M University System, 6/1/2012 –Present
Training Director, Emergency Services Training Institute, Texas Engineering Extension
Service, Texas A&M University System, 1/1/2012 – 5/31/2012
Training Manager, Emergency Services Training Institute, Texas Engineering Extension
Service, Texas A&M University System, 10/1/2007 – 12/31/2011
Program Coordinator, Emergency Services Training Institute, Texas Engineering
Extension Service, Texas A&M University System, 5/1/2007 – 9/30/2007
Training Coordinator, Emergency Services Training Institute, Texas Engineering
Extension Service, Texas A&M University System, 10/1/2004 – 4/31/2007
Instructor, Emergency Services Training Institute, Texas Engineering Extension Service,
Texas A&M University System, 2/1/2002 – 9/30/2004
197
Hazardous Materials Training Program Coordinator, Kentucky Division of Emergency
Management, Commonwealth of Kentucky, 5/1/2000 – 1/31/2002
UNIVERSITY TEACHING
Instructor, Adelphi University, Garden City, NJ
University College
 UEM 308 – Emergency Services Leadership (Spring 2013)
 UEM 306 – Master Planning for Public Emergency Management (Fall 2012)
Co-Instructor, Texas A&M University, College Station, TX
The Dwight Look College of Engineering
Safety Engineering Program
Course Instruction: (with Jason Loyd)
 SENG 422/677 – Fire Protection Engineering (Fall 2012; Fall 2013)
Instructor, Texas A&M University, College Station, TX
The Bush School of Government and Public Service
Certificate in Homeland Security
Course Instruction:
 INTA 689 – Foundational Readings in National Preparedness (Spring 2009)
 PPSA 689 - Foundational Readings in National Preparedness (Spring 2010)
Co-Instructor, Texas A&M University, College Station TX, 2008
Educational Administration Program
Department of Education Administration and Human Resource Development, College of
Education and Human Development
Course Instruction (With Dr. Fred Bonner):
 EDAD 601: College Teaching
JUNIOR/COMMUNITY COLLEGE TEACHING
Guest Instructor, 1986-1991
 Vincennes University – Jasper Center, Jasper, IN, Emergency Medical Technician
 Vincennes University, Vincennes, IN, Emergency Medical Technician
REFEREED PUBLICATIONS
Moats, J. & McLean, G.N. (2009). Speaking our language: The Essential Role of ScholarPractitioners in HRD. Advances in Developing Human Resources. 11(4), 507-522.
Moats, J., Chermack, T.J., & Dooley, LM. (2008). Using scenarios to develop crisis
managers: Applications of scenario planning and scenario-based training. Advances
in Developing Human Resources. 10(3), 397-424.
198
REFEREED CONFERENCE PROCEEDINGS
Moats, J. (2009). Human Resource Development and Homeland Security: HRD’s role in
securing the homeland. Presentation presented at the AHRD 2009 International
Research Conference, Arlington, VA.
Rolle, A., Kenzhegaranova, M., Fowler, R., Reid, G., & Moats, J. (2008). Five reflections
on the 2007 AHRD International Research Conference. Paper presented at the
AHRD 2008 International Research Conference, Panama City, FL.
INVITED PRESENTATIONS AND PAPERS
McWhorter, R., Moats, J., and Mancuso, D. (2009). Research workshop on national security
human resource development. Invited presentation for the Project on National
Security Reform and George Washington University, Alexandria, VA.
Plourde, K. & Moats, J (2007). The incident command system: A process to move our
response stance from reactive to proactive. The Coast Guard Proceedings of the
Marine Safety and Security Council. 63(4), 11-14.
Moats, J. (2002). Learning lessons: After action reports. Firehouse.com (online publication.
http://cms.firehouse.com/web/online/Training/Learning-Lessons--After-ActionReports/40$98).
CONFERENCE PRESENTATIONS
Rolle, A., Kenzhegaranova, M., Fowler, R., Reid, G., & Moats, J. (2008). Five reflections
on the 2007 AHRD International Research Conference. Paper presented at the
AHRD 2008 International Research Conference, Panama City, FL.
Moats, J. (2010). Case Studies: Tools to Learn By. Presentation presented at the 2010
International Association of Emergency Managers Annual Conference, San Antonio,
TX.
Moats, J. (2009). Reaching Beyond the Classroom: Using Virtual Worlds to Conduct
Training. Presentation presented at the 2009 International Association of Emergency
Managers Annual Conference, Orlando, FL.
Moats, J. (2004). Terrorism in the Barnyard. Presentation presented at the 2004 Kentucky
Emergency Services Conference, Lexington, KY.
Moats, J. (2004). National Incident Management System. Presentation presented at the 2004
Kentucky Emergency Services Conference, Lexington, KY.
Moats, J. (2004). Lessons Learned from Major Incidents. Presentation presented at the 2004
Kentucky Emergency Services Conference, Lexington, KY.
Moats, J. (2004). Terrorism in the Barnyard. Presentation presented at the 2004 Fire
Department Instructor’s Conference, Indianapolis, IN.
Moats, J. (2003). Terrorism in the Barnyard. Presentation presented at the 2003 Fire
Department Instructor’s Conference, Indianapolis, IN.
REVIEWER
Conferences:
Academy of Human Resource Development (AHRD) International Research
Conference, 2007-present.
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Journals:
Journal of European Industrial Training, September 2008 - present
BOOKS
Moats, J. B., (2007). Agroterrorism: A guide for emergency responders, Texas A&M
University Press, College Station, TX
COURSES DEVELOPED
Sports and Special Events Incident Management TEEX
Course Manager/SME
Managing Critical Incidents for Higher
Education Institutions: A Multi-disciplinary,
Community Approach
TEEX
Development Manager/SME
Incident Command Systems Forms Review
TEEX
Course Manager/SME
Advanced Incident Management
/ Unified Command
TEEX
Course Manager/SME
INTA 689 – Foundational Readings in National Preparedness TAMU
Co-author/SME
Intermediate Concepts of Incident Command
TEEX
Lead Author/Lead SME
Advanced Concepts of Incident Command
TEEX
Lead Author/Lead SME
WMD Enhanced – IM/UC
TEEX
Lead Author/Lead SME
WMD Incident Management Unified Command TEEX
(rewrite) Contributing author
WMD Incident Management Concepts
TEEX
Contributing author
WMD Awareness Internet Course WMD 0005 TEEX
Lead author/Lead SME
WMD Defensive Operations
TEEX
Lead author/Lead SME
Hazardous Materials Awareness
University of Louisville Author/Designer
KYERC Incident Management System
Commonwealth of Kentucky
Author
KYERC Hazardous Materials Awareness
Commonwealth of Kentucky
Author
KYERC Hazardous Materials Operations
Commonwealth of Kentucky
Author
PROFESSIONAL SERVICE
Chair, Scholar-Practitioner Special Interest Group (SIG), Academy of Human Resource
Development, 2011-2013
Fellow, Integrated Center for Homeland Security, Texas A&M University, 2008-2009
Member, U.S. Department of Homeland Security Target Capabilities Working Group
(Emergency Operations Center), 2008-2010
Member, U.S. Department of Homeland Security Target Capabilities Working Group
(Onsite Incident Management), 2007-2010
PROFESSIONAL AFFILIATIONS
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Academy of Human Resource Development
American Evaluation Association
American Society for Training and Development
Project Management Institute
AWARDS, HONORS, CERTIFICATIONS
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Certificate in College Teaching, Texas A&M University, 2009
Certificate in Homeland Security, Texas A&M University, 2008
Certified Training and Development Professional, Texas A&M University, 2008
Certified Instructor, National Domestic Preparedness Consortium, 2003
Certified Technical Trainer, Comp TIA, 2002
Certified Hazardous Materials Manager - Master, International Association of Certified
Hazardous Materials Managers, 2002-2008
Honorable Discharge, United States Navy, 1996
Navy and Marine Corps Achievement Medal, United States Navy, 1996
Valor Award, Escambia County (FL) Firefighters Association, 1993
Award of Valor, Warrington (FL) Fire Department, 1993
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